Project: Conduct Quantitative Analysis
>Quantitative Analysis
Awais Khan &D &P
&A
Awais Khan &D &P
Apply Quantitative Reasoning w that you have completed your analysis, think about the patterns you have seen in the workforce. 1, 00–$1 ,000 or $1 1,000–$ 0,000. This may indicate a reasonable promotion rate for new and seasoned employees. Is this distribution unimodal or bimodal? Please explain. 000 and $ . The income then stabilizes in an increasing manner then begins tto drastically decrease. The abnormal spikes even though steadies after a while indicates a bimodal method of distribution thru 202 . Hint: An easy way to do this is to highlight the sales from the data page and apply the Forecast tool to this data or use the forecast function in excel. You will generate a chart on a new sheet with projected sales; rename this sheet “Projected “. , Hryly Rate, s Worked, ucation, and . What does this tell you about the variables? 0000 and $ 000. this is evident from the calculated mean of $9967 . This however is contrasted by the hourly late of $ paid to the employees. This is an indication that majority of the employee have an average living while the lower band get a much less pay. The employees have a score of 9.94 in age per year. This therefore shows the close corelation between the salries paid the age, hourly rate and the years worked in the company. , mean for the variable of Salary? What are the standard deviations for the other variables and what do they mean? 4. The company has a keen interest in the educational, race, and gender makeup of its workforce. Its emphasis is on a diverse, dynamic workforce. From your “Graph Charts” spreadsheet, describe your pie chart findings for these characteristics of the workforce. Describe how you would determine if the company was meeting expectations on these characteristics. of the employees are male and only % are female. This can help the company to consider hiring more female employees. Also they need to create a balance and a diversity in the marital status of its employees. VER asked if the comapny was diverse. You were NEVER asked what the company could do to become more diverse. You were simply asked to describe the process of analysis. HOW would you determine IF the company were diverse. How?? What process would you follow to analyze the information. This question is essentially asking you to figure out how you would analyze the data for the essay. 5. The company is conducting an analysis on how many positions to create to keep up with demand. Specifically, it wants to know an estimate of the number of positions per job title. From your Excel chart, identify the mode of the job title distribution. Describe your findings. in Company Acctg/Fin 12 3 6 1 1 1 1 6 8 3 8 2 18 5 1 5 18 14 1 5 2 1 3 Cyber Mgr 8 Sr Public and Business Office Team Mgr 3 FEEDBACK: You did not answer the question. You were simply asked for the MDOE of the job titles. The mode is the item in a population that occurs the most frequently. The population for this question is the list of job titles, so which job title occurs the most? Now that you have done all the work with data, you will write a short three- to four-paragraph summary of your analysis. This is important. While you have done a wonderful job with your analysis, you can never assume that the end user will be able to interpret the data the way it should be understood. Supporting narrative is helpful. Never simply provide a “raw data” dump. Instead, seek to provide information! shows a steady curve with the possibility of a steady drop or rise in sales. Based on the forecast data it is safe to say that with all factors held constant the company will contiue to make steady profits but with adverse effects in the company it is possible to make huge losses or better profits. Therefore it is advisable for the company to seek other ways to motivate its employees such as internal promotions. This ensure that there is maximuma co-orporation of employees thus yielding better results. Also the average salary for the company is about $ which is a good opportunity for the employees to work in. s, but that this has stagnated and has been holding steady or slightly declining for the last 4 years. You can look at the projections and determine that the company seems to be more focused on hiring African Americans and a slight focus on hiring s. Based on this, maybe the company is implementing changes in their hiring practices. Maybe the company is advertising in communities with a higher number of minorities instead of advertising positions in the more caucasian environments. This is something you could ask for. This is analysis. Find the pattern, determine if it is significant, and then identify the information that is relevant to the pattern but currently missing and needed to complete the analysis. This is the type of work you need to do to get a passing grade on this assignment.
Currency Number General Number General Number Number Number General Yr
/ 10 Salary Ed Age Vested 00
Sr Cyber Investigator . 5 19 No 3 1 1 /02
Cyber Analyst 1,801
.75
16 60 3 1 1 IL Midwest /18
Forensics Analyst 8
.60
1 16 23 No 1 2 2 Cyber Analyst 5
10 14 43 No 1 1 1 NE /11
Cyber Analyst . 8 19 44 No 3 1 1 IL Midwest Forensics Analyst ,1 8 19 31 No 1 1 1 IL Midwest Cyber Analyst 5
.73
8 16 40 No 3 1 2 PA Northeast Cyber Analyst 8
9 14 39 No 1 1 1 PA Northeast /04
Cyber Analyst 16 16 53 Yes 3 1 1 PA Northeast Advertising , 4
.72
6 16 28 No 1 2 2 NE C-Plains Cyber Mgr 5 16 38 No 3 1 1 PA Northeast Sr Cyber Investigator . 13 16 51 Yes 1 1 1 NE C-Plains Cyber Analyst 9 14 36 No 4 1 2 IL Midwest IT Staff 8 16 51 No 3 1 1 IL Midwest Cyber Software Engineer 6 16 39 No 3 1 1 PA Northeast IT Staff 14 19 Yes 3 1 1 PA Northeast Forensics Analyst 6 14 25 No 3 1 2 PA Northeast Cyber Analyst , 0
8 16 40 No 1 1 1 PA Northeast Cyber Analyst 1
7 16 30 No 3 1 2 PA Northeast Cyber Analyst ,219
4 14 35 No 3 1 2 NE C-Plains Physical Security 4 12 25 No 3 2 2 NE C-Plains Cyber Analyst .76
13 16 Yes 1 1 1 PA Northeast IT Staff 2 14 31 No 1 2 2 PA Northeast Sr Cyber Investigator 8 19 No 3 1 1 IL Midwest Cyber Analyst 8 16 34 No 3 1 2 PA Northeast Cyber Analyst 4 16 36 No 4 1 2 PA Northeast Malware Reverse Engineer 7 16 49 No 2 1 2 PA Northeast Cyber Analyst 16 16 59 Yes 3 1 1 IL Midwest Forensics Analyst 3 16 28 No 1 1 1 PA Northeast Forensics Analyst 3 14 25 No 3 1 2 IL Midwest Cyber Analyst 10 16 51 Yes 1 1 1 PA Northeast Cyber Analyst 4 16 37 No 3 1 1 IL Midwest Cyber Analyst 12 14 51 Yes 3 1 1 PA Northeast Public and Business Office Team 2 16 34 No 3 2 1 IL Midwest Cyber Software Engineer 3 16 36 No 3 1 1 PA Northeast Cyber Analyst ,641
4 14 33 No 4 1 2 IL Midwest Forensics Analyst 11 16 36 Yes 3 1 1 PA Northeast Cyber Analyst 9 19 47 No 3 1 2 NE C-Plains Cyber Analyst 15 16 52 Yes 3 1 1 PA Northeast Cyber Analyst 13 16 53 Yes 1 1 2 IL Midwest Logistics 11 16 51 Yes 3 2 1 PA Northeast Public and Business Office Team 3 16 57 No 3 1 1 IL Midwest Cyber Analyst 6 19 34 No 3 1 1 PA Northeast IT Mgr $154,933 2 16 24 No 3 1 1 IL Midwest Cyber Analyst 3 16 26 No 3 1 2 IL Midwest Sr Cyber Investigator 6 16 34 No 3 1 1 IL Midwest Cyber Analyst 8 16 36 No 2 1 1 NE C-Plains Cyber Analyst 5 16 39 No 2 1 1 IL Midwest Cyber Analyst 3 16 34 No 4 1 1 NE C-Plains Cyber Analyst 17 14 56 Yes 3 1 1 PA Northeast Forensics Analyst 8 16 31 No 4 1 1 PA Northeast Acctg/Fin 3 19 28 No 1 1 2 PA Northeast 2/24/16 Forensics Analyst 4 16 26 No 3 1 2 NE C-Plains Cyber Analyst 11 16 52 Yes 3 1 1 NE C-Plains Cyber Analyst 6 16 41 No 3 1 1 IL Midwest Sr Cyber Investigator 2 16 31 No 4 2 1 IL Midwest Cyber Analyst 8 16 41 No 1 1 1 PA Northeast Cyber Analyst 2 16 28 No 3 2 2 IL Midwest Physical Security 2 12 22 No 1 1 1 IL Midwest Cyber Analyst 7 16 41 No 1 1 1 NE C-Plains Public and Business Office Team 18 19 68 Yes 3 1 1 NE C-Plains Cyber Analyst 5 14 38 No 1 1 1 IL Midwest Cyber Analyst 14 16 51 Yes 1 1 1 NE C-Plains Acctg/Fin 6 14 40 No 3 2 1 PA Northeast Cyber Software Engineer $162,731 $78.24 8 16 54 No 3 1 1 NE C-Plains Cyber Analyst 2 14 28 No 3 1 1 IL Midwest Sr Cyber Investigator 8 16 39 No 1 1 2 PA Northeast 7/15/03 Cyber Analyst 16 12 59 Yes 3 1 1 IL Midwest IT Staff 5 16 38 No 1 1 1 NE C-Plains Sr Public and Business Office Team Mgr 2 16 57 No 1 1 1 IL Midwest Physical Security 9 14 42 No 1 2 1 PA Northeast Acctg/Fin 15 16 49 Yes 3 1 2 NE C-Plains Sr Cyber Investigator 4 16 32 No 1 2 1 PA Northeast Forensics Analyst 3 14 27 No 3 1 2 IL Midwest Cyber Analyst $72.68 7 16 38 No 3 1 1 NE C-Plains Cyber Analyst 6 14 43 No 1 1 1 IL Midwest Cyber Analyst 5 14 40 No 4 2 1 IL Midwest Cyber Analyst 6 14 37 No 3 1 1 NE C-Plains IT Staff 4 14 26 No 3 1 1 IL Midwest Public and Business Office Team 1 16 37 No 3 1 1 NE C-Plains Advertising $145,776 $70.08 7 19 30 No 3 2 2 IL Midwest Cyber Analyst 13 14 50 Yes 3 1 1 IL Midwest Cyber Analyst 13 16 54 Yes 3 1 1 PA Northeast 7/10/11 8 19 40 No 3 2 2 IL Midwest Quality Assurance 15 16 54 Yes 3 1 1 PA Northeast Cyber Analyst 7 16 34 No 1 2 1 IL Midwest IT Staff 5 16 41 No 3 2 1 IL Midwest Malware Reverse Engineer 2 16 27 No 1 1 2 PA Northeast Investigator 3 16 33 No 3 1 2 IL Midwest Forensics Analyst 0 16 21 No 1 1 2 IL Midwest Sr Cyber Investigator 12 16 43 Yes 1 1 1 PA Northeast Forensics Analyst 4 16 28 No 1 1 1 PA Northeast Malware reverse engineer $41.53 6 14 40 No 1 1 2 IL Midwest Cyber Mgr 16 19 51 Yes 3 2 1 PA Northeast Cyber Analyst 7 14 44 No 1 1 1 IL Midwest Forensics Analyst 15 16 40 Yes 3 1 1 PA Northeast Cyber Analyst 4 14 27 No 3 1 2 IL Midwest Cyber Analyst 7 16 30 No 3 1 2 NE C-Plains Sr Cyber Investigator 8 16 41 No 3 1 1 PA Northeast Admin $37.92 5 12 36 No 1 2 2 PA Northeast Cyber Analyst 5 16 30 No 3 1 1 NE C-Plains Cyber Analyst 9 14 40 No 4 1 1 NE C-Plains Investigator 2 19 31 No 2 1 1 IL Midwest Forensics Analyst 9 14 36 No 1 1 1 PA Northeast Cyber Analyst 9 16 40 No 1 1 1 IL Midwest Cyber Analyst 6 14 35 No 3 1 2 PA Northeast Cyber Analyst 4 16 39 No 3 1 1 IL Midwest Cyber Analyst 12 16 53 Yes 2 1 1 NE C-Plains Logistics 12 16 49 Yes 3 1 2 PA Northeast Cyber Analyst 9 16 38 No 4 1 1 NE C-Plains Cyber Analyst 1 16 27 No 1 2 1 PA Northeast Sr Forensics Mgr 6 19 40 No 1 1 1 NE C-Plains Marketing 3 16 37 No 3 2 1 IL Midwest Cyber Software Engineer 2 19 34 No 2 1 1 PA Northeast Cyber Software Engineer 14 16 51 Yes 3 1 1 NE C-Plains Cyber Analyst 3 16 31 No 3 1 1 PA Northeast Sr Cyber Investigator 12 16 46 Yes 3 1 2 IL Midwest Cyber Analyst 9 19 41 No 3 1 1 PA Northeast Cyber Analyst 4 16 31 No 3 1 1 IL Midwest Physical Security 9 16 46 No 1 1 1 PA Northeast Cyber Analyst 14 19 59 Yes 1 1 1 IL Midwest Sr Cyber Analyst ,466
2 16 31 No 4 1 1 IL Midwest Forensics Analyst 6 19 34 No 3 1 2 IL Midwest Public and Business Office Team 9 14 58 No 4 1 1 IL Midwest Cyber Analyst 8 14 39 No 3 1 1 NE C-Plains Malware Reverse Engineer 8 16 54 No 3 1 1 PA Northeast Cyber Analyst 10 19 47 No 4 1 2 PA Northeast Cyber Analyst 4 16 30 No 1 1 2 NE C-Plains Cyber Analyst 15 19 53 Yes 3 1 1 PA Northeast Cyber Software Engineer 9 19 56 No 3 1 1 PA Northeast Logistics Mgr 4 16 53 No 1 1 1 IL Midwest Cyber Analyst 8 16 38 No 4 1 1 PA Northeast Public and Business Office Team 2 16 40 No 4 1 1 NE C-Plains Forensics Analyst 6 16 26 No 1 1 1 NE C-Plains 9/4/06 Investigator 13 16 51 Yes 3 1 1 NE C-Plains Cyber Software Engineer 3 12 31 No 2 1 1 PA Northeast Acctg/Fin 17 14 62 Yes 1 1 1 NE C-Plains Cyber Analyst $150,263 $72.24 13 12 53 Yes 2 1 1 NE C-Plains Sr Cyber Investigator 13 19 53 Yes 3 1 1 NE C-Plains Forensics Analyst 9 16 30 No 4 1 1 IL Midwest Cyber Mgr 2 14 40 No 3 2 1 IL Midwest Cyber Analyst $156,750 $75.36 14 16 51 Yes 3 1 2 NE C-Plains Cyber Analyst $151,523 $72.85 12 16 56 Yes 1 1 1 IL Midwest Cyber Software Engineer 3 14 25 No 3 2 1 NE C-Plains Cyber Analyst 8 16 44 No 3 1 1 IL Midwest Public and Business Office Team Mgr 8 12 47 No 3 1 1 PA Northeast Eng Mgr 10 14 44 Yes 3 1 1 NE C-Plains Malware Reverse Engineer 11 19 49 Yes 3 1 2 IL Midwest COO $154,933 $74.49 11 19 43 Yes 3 1 2 IL Midwest Public and Business Office Team 4 19 61 No 4 1 1 PA Northeast Public and Business Office Team $57.29 5 16 41 No 3 1 1 PA Northeast Admin 4 16 37 No 4 1 2 IL Midwest Forensics Analyst 2 14 21 No 3 1 2 NE C-Plains Public and Business Office Team $34.47 2 14 32 No 3 1 1 PA Northeast Advertising 7 14 39 No 3 2 2 PA Northeast Cyber Analyst 7 16 37 No 3 1 1 PA Northeast IT Staff 16 16 55 Yes 1 1 1 PA Northeast Acctg/Fin 1 16 25 No 3 2 1 NE C-Plains Cyber Software Engineer 7 19 44 No 2 1 2 NE C-Plains Sr Cyber Investigator 7 19 37 No 1 1 2 IL Midwest Cyber Analyst 11 14 43 Yes 3 1 1 PA Northeast Cyber Analyst 8 14 41 No 2 1 1 IL Midwest Cyber Analyst $32.80 5 19 29 No 3 1 2 PA Northeast Cyber Software Engineer 5 19 42 No 3 2 1 IL Midwest IT Staff 3 19 36 No 2 1 1 PA Northeast 7/11/04 CEO 15 19 58 Yes 3 1 1 PA Northeast Cyber Analyst 13 16 57 Yes 2 1 1 PA Northeast Logistics $30.87 5 16 34 No 3 1 1 IL Midwest 6/20/15 Cyber Analyst 5 14 29 No 1 1 1 NE C-Plains Sr Public and Business Office Team Mgr 4 16 51 No 3 2 1 NE C-Plains Cyber Analyst 10 16 45 No 3 1 1 PA Northeast IT Staff 10 14 50 No 3 1 1 NE C-Plains Public and Business Office Team 3 16 37 No 1 2 1 IL Midwest Controller 15 19 50 Yes 3 2 1 IL Midwest Forensics Analyst 10 16 32 Yes 3 2 2 IL Midwest Cyber Analyst 16 16 57 Yes 1 1 1 NE C-Plains Public and Business Office Team 5 19 45 No 1 1 2 NE C-Plains Cyber Analyst 7 16 37 No 1 1 1 IL Midwest Physical Security 8 14 39 No 1 2 1 IL Midwest Investigator 14 16 39 Yes 3 1 1 NE C-Plains Cyber Software Engineer $152,446 $73.29 11 16 54 Yes 3 1 1 NE C-Plains 8/13/17 Cyber Analyst 2 16 25 No 1 2 2 IL Midwest Sr Cyber Investigator $156,750 $75.36 13 16 61 Yes 1 1 2 NE C-Plains Cyber Analyst 11 16 54 Yes 1 1 1 IL Midwest Public and Business Office Team 1 14 35 No 3 1 2 PA Northeast Cyber Analyst 14 19 58 Yes 1 1 1 PA Northeast Cyber Analyst 6 16 37 No 1 1 2 PA Northeast Cyber Analyst 13 16 48 Yes 3 1 1 PA Northeast Logistics 5 16 38 No 3 2 1 PA Northeast Sr Cyber Investigator 3 16 33 No 1 1 1 IL Midwest Acctg/Fin 5 16 35 No 1 2 1 NE C-Plains Cyber Software Engineer $164,033 $78.86 2 14 30 No 3 1 1 IL Midwest Cyber Analyst 9 16 46 No 3 1 1 NE C-Plains Forensics Analyst 6 16 28 No 3 1 2 IL Midwest Acctg/Fin 7 12 48 No 3 1 1 NE C-Plains Cyber Analyst 9 16 40 No 1 1 2 NE C-Plains Forensics Analyst 6 16 24 No 4 1 1 NE C-Plains Cyber Mgr 18 14 48 Yes 4 2 1 IL Midwest Quality Assurance 2 16 35 No 3 1 1 NE C-Plains Cyber Analyst 6 16 38 No 3 1 2 NE C-Plains Cyber Software Engineer 7 16 42 No 2 2 1 NE C-Plains Investigator 7 16 36 No 4 2 1 PA Northeast 12/4/11 Malware Reverse Engineer 8 19 40 No 3 1 1 NE C-Plains IT Mgr 6 19 56 No 3 1 1 PA Northeast Physical Security 3 14 30 No 2 2 1 IL Midwest Cyber Analyst $49.87 8 14 46 No 3 1 1 NE C-Plains Cyber Analyst 11 19 49 Yes 3 2 1 PA Northeast Cyber Analyst 11 19 49 Yes 1 1 2 NE C-Plains Forensics Analyst 2 14 26 No 3 1 2 NE C-Plains CIO 16 19 50 Yes 3 1 1 NE C-Plains Sr Cyber Investigator 4 19 38 No 1 2 1 IL Midwest Physical Security 3 14 24 No 1 2 2 PA Northeast Physical Security $43,367 $20.85 4 16 34 No 3 1 1 IL Midwest Cyber Analyst 14 16 55 Yes 3 1 1 IL Midwest Eng Mgr 10 12 49 Yes 3 1 2 PA Northeast Cyber Analyst $148,111 $71.21 7 14 33 No 3 1 1 PA Northeast Forensics Analyst 1 16 22 No 1 1 2 NE C-Plains Physical Security 2 12 22 No 3 2 2 IL Midwest Cyber Analyst 9 16 41 No 3 1 1 PA Northeast IT Staff 4 16 28 No 3 1 1 PA Northeast Advertising 7 16 34 No 3 1 2 NE C-Plains Cyber Analyst $38.26 16 14 55 Yes 3 1 1 IL Midwest Cyber Analyst $42.08 18 14 57 Yes 3 1 1 IL Midwest IT Staff 12 16 46 Yes 2 1 1 PA Northeast Cyber Analyst 8 12 43 No 3 1 1 IL Midwest Sr Cyber Investigator 9 19 40 No 3 1 1 NE C-Plains Cyber Analyst 9 16 51 No 3 1 1 IL Midwest 7/16/01 Cyber Analyst 18 16 60 Yes 1 1 2 PA Northeast Cyber Analyst 12 14 46 Yes 1 1 1 PA Northeast 7/11/03 Cyber Analyst 16 14 55 Yes 3 1 1 PA Northeast Sr Forensics Mgr 4 16 48 No 3 1 1 IL Midwest Investigator 10 16 33 Yes 3 2 1 IL Midwest Cyber Analyst 8 14 44 No 1 1 1 PA Northeast Cyber Analyst 6 16 44 No 1 1 1 PA Northeast Sr Cyber Investigator $46.43 10 19 46 Yes 3 1 1 PA Northeast Cyber Analyst 4 16 28 No 4 1 1 IL Midwest 7/20/01 Sr Cyber Investigator 18 16 65 Yes 3 1 1 PA Northeast 11/10/11 Forensics Analyst 8 16 31 No 1 1 1 PA Northeast 7/17/02 Investigator 17 14 53 Yes 3 1 1 NE C-Plains Cyber Mgr 4 16 36 No 4 1 1 NE C-Plains IT Staff $42.02 13 14 51 Yes 1 1 1 NE C-Plains Cyber Software Engineer 9 19 42 No 3 1 1 NE C-Plains Cyber Software Engineer 7 16 44 No 3 2 1 IL Midwest Malware Reverse Engineer 9 16 34 No 3 1 1 NE C-Plains Cyber Analyst 1 16 27 No 3 2 1 IL Midwest Malware Reverse Engineer 5 16 34 No 3 1 2 IL Midwest Investigator 12 16 34 Yes 1 1 1 IL Midwest Sr Cyber Investigator 15 16 57 Yes 3 2 1 PA Northeast Sr Cyber Investigator $152,446 $73.29 7 16 37 No 3 1 1 PA Northeast Marketing 2 16 42 No 3 2 1 PA Northeast Forensics Analyst 7 19 30 No 3 1 1 IL Midwest 12/29/17 Cyber Software Engineer $151,174 $72.68 2 16 40 No 3 2 1 PA Northeast Forensics Analyst 7 19 29 No 4 1 1 IL Midwest Cyber Analyst 4 16 27 No 3 1 1 PA Northeast Cyber Analyst 6 14 37 No 1 1 1 IL Midwest Physical Security $43,367 $20.85 7 16 29 No 3 1 2 NE C-Plains Cyber Software Engineer 5 19 44 No 3 1 1 PA Northeast Quality Assurance 6 16 40 No 3 1 1 IL Midwest Physical Security $43,367 $20.85 5 16 33 No 3 1 1 IL Midwest Sr Cyber Investigator 11 16 39 Yes 4 1 1 PA Northeast Sr Cyber Investigator 9 19 40 No 4 1 1 NE C-Plains Malware Reverse Engineer 1 14 39 No 2 1 2 IL Midwest Cyber Analyst 8 16 39 No 3 1 2 PA Northeast Physical Security 4 14 30 No 3 2 1 PA Northeast Cyber Analyst 4 16 35 No 4 1 2 PA Northeast Cyber Analyst $88,743 $42.66 5 19 33 No 2 2 2 IL Midwest Cyber Analyst 2 16 25 No 3 1 2 PA Northeast Cyber Analyst 9 16 50 No 3 1 1 NE C-Plains Cyber Mgr $30.74 5 19 42 No 3 2 1 PA Northeast IT Staff 6 14 43 No 1 1 1 PA Northeast Forensics Analyst $143,063 $68.78 7 16 31 No 1 1 2 NE C-Plains Cyber Analyst 6 14 34 No 1 2 1 PA Northeast Physical Security 6 12 27 No 1 1 2 PA Northeast Forensics Analyst 4 14 35 No 1 1 2 NE C-Plains Cyber Analyst 10 19 41 Yes 1 1 1 PA Northeast Cyber Analyst 13 16 58 Yes 3 1 1 PA Northeast IT Staff 8 19 35 No 3 1 1 PA Northeast Sr Public and Business Office Team Mgr 5 14 56 No 3 1 2 PA Northeast Sr Cyber Investigator 15 16 55 Yes 1 1 1 PA Northeast CFO 7 16 48 No 4 1 2 IL Midwest Acctg/Fin 15 14 42 Yes 3 2 2 NE C-Plains Cyber Analyst $40.11 7 16 38 No 3 1 1 PA Northeast Acctg/Fin 7 16 44 No 3 1 1 PA Northeast Admin $41.85 3 14 25 No 3 2 2 PA Northeast Quality Assurance 3 16 45 No 3 2 2 IL Midwest Cyber Analyst 12 16 50 Yes 1 1 1 IL Midwest Cyber Software Engineer 3 16 28 No 1 2 2 NE C-Plains 10/4/12 Cyber Analyst 7 19 35 No 3 1 1 PA Northeast Forensics Analyst 7 16 31 No 3 1 1 PA Northeast Cyber Software Engineer 5 16 38 No 3 1 1 PA Northeast Malware Reverse Engineer 6 16 37 No 3 2 1 NE C-Plains Cyber Analyst $162,731 $78.24 5 16 32 No 1 1 1 PA Northeast Logistics 4 19 36 No 3 2 1 IL Midwest Public and Business Office Team 7 14 44 No 2 2 1 PA Northeast IT Staff 5 14 37 No 3 1 1 NE C-Plains Marketing 6 19 40 No 1 1 1 IL Midwest 6/24/13 Acctg/Fin 7 14 38 No 2 1 2 NE C-Plains IT Staff 17 19 52 Yes 3 1 1 IL Midwest Sr Cyber Analyst $154,122 $74.10 1 19 33 No 1 1 2 IL Midwest Cyber Software Engineer 8 16 45 No 3 1 1 PA Northeast Forensics Analyst $154,933 $74.49 8 16 31 No 1 1 1 NE C-Plains IT Staff $141,110 $67.84 7 16 36 No 3 1 1 IL Midwest 7/11/03 Malware Reverse Engineer 16 14 63 Yes 3 1 1 PA Northeast 5/3/13 Physical Security 7 16 34 No 3 2 1 PA Northeast Cyber Analyst 6 16 28 No 3 1 2 NE C-Plains Cyber Analyst 8 14 34 No 3 1 1 NE C-Plains Forensics Analyst 9 16 32 No 1 1 1 NE C-Plains Forensics Analyst $47.66 9 14 35 No 3 1 1 IL Midwest Cyber Analyst 10 19 42 No 2 1 1 IL Midwest Cyber Analyst 12 12 47 Yes 3 1 1 PA Northeast Acctg/Fin 2 16 30 No 3 1 1 PA Northeast Cyber Software Engineer 3 16 29 No 2 2 2 PA Northeast 12/14/13 Cyber Analyst 6 19 43 No 3 1 1 NE C-Plains Sr Cyber Investigator 16 19 61 Yes 1 2 1 PA Northeast Cyber Analyst $148,111 $71.21 10 16 39 No 3 1 1 NE C-Plains Forensics Analyst 3 12 26 No 3 1 2 PA Northeast Physical Security 8 14 45 No 3 2 1 PA Northeast Malware Reverse Engineer 2 16 36 No 3 1 2 NE C-Plains Cyber Analyst 11 16 47 Yes 3 1 1 NE C-Plains Cyber Mgr 1 16 34 No 1 2 1 IL Midwest 2/6/14 Forensics Analyst 6 16 42 No 3 1 1 NE C-Plains Cyber Analyst $41.85 6 14 34 No 2 1 1 IL Midwest Physical Security 7 16 44 No 3 1 1 NE C-Plains 7/11/04 Cyber Software Engineer 15 16 59 Yes 3 1 1 PA Northeast Malware Reverse Engineer 4 16 27 No 4 2 2 IL Midwest Cyber Analyst $71.86 9 16 42 No 3 1 1 PA Northeast Physical Security 6 12 29 No 1 1 1 PA Northeast Cyber Analyst $149,466 $71.86 5 19 30 No 3 1 1 PA Northeast Public and Business Office Team 5 16 42 No 3 2 1 PA Northeast Eng Mgr $172,291 $82.83 5 16 52 No 3 1 1 NE C-Plains Cyber Analyst 14 14 49 Yes 1 2 2 PA Northeast IT Staff $33.49 2 16 24 No 2 2 1 PA Northeast Cyber Analyst 8 16 43 No 4 2 1 IL Midwest Cyber Analyst 3 16 27 No 3 1 2 IL Midwest Advertising 17 16 60 Yes 3 1 1 PA Northeast Forensics Analyst 8 14 31 No 1 2 1 PA Northeast 3/30/11 Cyber Analyst $39.08 9 14 44 No 3 1 1 IL Midwest Sr Forensics Mgr 8 14 41 No 3 1 1 PA Northeast Advertising $144,571 $69.51 17 16 39 Yes 3 1 1 IL Midwest Marketing 12 19 47 Yes 3 2 1 PA Northeast Acctg/Fin $154,122 $74.10 9 12 49 No 3 2 2 PA Northeast Cyber Analyst 8 16 44 No 3 1 1 IL Midwest Quality Assurance 6 16 52 No 1 2 1 NE C-Plains Cyber Software Engineer $140,865 $67.72 2 14 30 No 3 1 2 NE C-Plains Cyber Mgr 9 16 39 No 1 1 1 IL Midwest Forensics Analyst 1 16 26 No 3 2 2 NE C-Plains Sr Cyber Investigator $44.27 14 14 47 Yes 2 1 1 IL Midwest Cyber Analyst 3 14 25 No 4 1 2 IL Midwest Cyber Analyst 8 19 31 No 1 1 1 IL Midwest Cyber Analyst 9 19 36 No 3 1 1 PA Northeast Cyber Analyst 7 16 35 No 3 1 2 IL Midwest Cyber Analyst 3 16 26 No 3 1 2 IL Midwest Malware Reverse Engineer 6 14 49 No 3 1 1 PA Northeast Sr Cyber Investigator 2 16 33 No 3 1 1 NE C-Plains 6/17/17 Cyber Analyst $143,005 $68.75 3 14 25 No 4 2 2 IL Midwest Cyber Analyst 14 16 52 Yes 3 1 2 NE C-Plains Forensics Analyst 5 16 29 No 4 1 2 PA Northeast Cyber Analyst 7 16 40 No 1 1 1 PA Northeast Cyber Analyst 2 14 25 No 1 1 1 PA Northeast Forensics Analyst 4 14 26 No 3 1 2 PA Northeast Cyber Analyst 11 19 50 Yes 3 1 1 PA Northeast Forensics Analyst $162,030 $77.90 6 12 31 No 4 1 2 IL Midwest Cyber Analyst 7 16 41 No 3 1 1 PA Northeast Cyber Analyst 15 16 54 Yes 2 1 1 PA Northeast Cyber Analyst 9 16 48 No 3 1 1 NE C-Plains Cyber Analyst $163,045 $78.39 8 16 50 No 1 1 1 PA Northeast Marketing 16 14 48 Yes 3 2 1 NE C-Plains Forensics Analyst $151,523 $72.85 12 16 34 Yes 3 1 2 PA Northeast Cyber Analyst 10 14 43 No 1 1 2 IL Midwest 1/19/18 Physical Security 2 14 24 No 1 2 1 NE C-Plains Malware Reverse Engineer 5 12 36 No 3 2 2 IL Midwest Cyber Analyst 9 14 37 No 3 1 2 IL Midwest mary Tables for Graphing
Sales Summary (Provided) # # % Yr Sales 98 0860215
33 100 77 # % 18 87 64 2020 # % 295 79.3010752688 77 20.6989247312 State Region # % State # % PA 149 40.0537634409 IL 125 33.6021505376 Descriptive Statistics Salary Hrly Rate Yrs of Svc Ed Age
2
1
No
In this final section, you will answer five questions and write a short essay.
1. From the created histogram, it appears that a large share of employees have a salary between $
6
0
10
3
1
7
Ans: The histogram indicates shows a gradual increase in employee salaries and a drastic increase between the salary bin $
60
70000
2. The line chart, as detailed in your “Graph Charts” Excel spreadsheet, shows sales generally increasing over the years, although sales in the first two years were notably lower. Assuming that the sales are linear, please use the Forecast tool to find projected sales for
2020
4
Sales
Ans: I have added the tab call (Projected Sales) for this question.
3. The standard deviation provides insight into the distribution of values around the mean. If the standard deviation is small, in general, the more narrow the range between the lowest and highest value. That is, values will cluster close to the mean. From your descriptive statistics, describe your standard deviations of
Salary
Yr
Ed
Age
Ans: Based on the salary structure the starndard deviation from the data apperas to be high. The salary band with the most employee appears to be $
9
100
5
15
FEEDBACK: First, there are FIVE standard deviations to discuss and you only touch on three of them. Also, saying the “standard deviation from the data appears to be high” doesn’t mean anything. What does having a standard deviation of $
32
8
52
Ans: The data indicates that the company has a less focus on the diversity of it’s employees both in terms of gender and race. This is dicated by the geographical location of the company which forces it to adapt to the environment and culture of the local people. The company can however considr in hiring new employees who are of different gender and race to balance the already existing imbalance. The most noticeable diversity is seen in the gender where 79
%
21
FEEDBACK: There are three pie charts and you need to describe with numerical and mathematical data all three of these pie charts. Not just the pie chart for gender. Additionally, you did not answer the second part of the question. You were
NE
Ans: Majority of the employees in the company are not in the managerial position and this can create a strain in the managerial team. Thus the comapany needs to hire more managers based on the data provided below. With the rate of growth of the ompany it is necessary to have enough senior employees to ensure that the junior employes are competent. Therefore it is inevitable for the company to evade hiring of new staff in the need to grow.
Key Emp
#
Acctg/Fin
12
Admin
Advertising
CEO
CFO
CIO
Controller
18
COO
Cyber Analyst
14
Cyber Mgr
Cyber Software Engineer
23
Eng Mgr
Forensics Analyst
39
Investigator
IT Mgr
IT Staff
Logistics
Logistics Mgr
Malware Reverse Engineer
16
Marketing
Physical Security
Public and Business Office Team
Public and Business Office Team Mgr
Quality Assurance
Sr Cyber Analyst
Sr Cyber Investigator
26
Sr Forensics Mgr
22
Sr Public and Business Office Team Mgr
Admin 3
Advertising 6
CEO 1
CFO 1
CIO 1
Controller 18
COO 1
Cyber Analyst 1
46
Cyber Software Engineer 23
Eng Mgr 3
Forensics Analyst 39
Investigator 8
IT Mgr 2
IT Staff 18
Logistics 5
Logistics Mgr 1
Malware Reverse Engineer 16
Marketing 5
Physical Security 18
Public and Business Office Team 14
Public and Business Office Team Mgr 1
Quality Assurance 5
Sr Cyber Analyst 2
Sr Cyber Investigator 26
Sr Forensics Mgr 122
Structure your essay like this:
a. Write a one-paragraph narrative summary of your findings, describing patterns of interest.
b. Provide an explanation of the potential relevance of such patterns.
c. Provide a description of how you would investigate further to determine if your results are “good or bad” for the company.
Prepare your response in this workbook. (Simply expand this text box to accommodate your essay and other answers, or you can copy and paste from another document.)
FINAL ESSAY:
Findings
The company’s forecast for 2020 to 20
24
100000
The company needs to ensure that there is diversity in terms or race, marital status and the gender of it’s employees. This eliminates discrimanation and domination of one group due to being the majority. Diversity creates a team work spirit and eliminates the unhealthy competitive nature of company employees. The company should also consider offering tuition courses or suggesting them to it’s employees so as employees can be motivated to apply for the top senior management jobs. This creates a steady and healty flow of employees and a professional culture work environment.
The data provided is however not sufficient to judge and place the company at it’s true position rather more analysis is needed to know the actual lace and position of the company both currently and in future. The analysis may involve how the drastic drift in diversity of employees may affect the company and how the salary mean and general statistics may interfere with employee perfomance. An analysis of how the company can best motivate it’s employees is also keen.
FEEDBACK: You have not analyzed the information or written an essay that is connected.:
– Paragraph 1: Identify a pattern of interest
– Paragraph 2: Explain why that pattern you identified is of interest
– Paragraph 3: What additional information do you need to be able to fully analyze the pattern
For paragraph 1, you identified a pattern with sales. Paragraph 2 is addressing diversity. The two are not related. Additionally, you have no information on the market, no data on economic demand, no information on productivity. In other words, you have no data with which to perform any kind of ecomonic analysis. All you have is HR data and a known interest in diversity, so that should be the focus of your analysis. Take a look at the screen shot to the right. I took a subset of the employees who are in a specific role, identified their year of hire, determined how many of each race were hired each year and then used the forecast tool to calculate the trend and projection. This is analysis. I can look at this and see that the hiring used to be focused on Caucasian
Asian
DATA
Workforce Profile Analysis
Section 1: Complete all Columns in Data Set
Format for:
Windows User: Format cells in column according to indicated format.
Number
Date
General
Currency
Text
mm/dd/yy
Year Ending
Vested
12/
31
19
Emp #
Hire Date
Role
Hrly Rate
Yrs of Svc
Race
Gender
Status
State
Region
40
4/23/15
$92,267
$
44
36
35
IL
Midwest
4004
7/
13
$
11
$
53
17
Yes
4010
11/
25
$90,
68
$
43
PA
Northeast
4012
1/26/10
$95,
98
$46.15
C-Plains
4013
12/
29
$100,520
$
48
33
4014
10/2/11
$
125
56
$60.17
4015
1/1/12
$78,
47
$
37
4020
5/9/11
$93,
51
$44.96
4022
5/
27
$69,529
$33.43
4023
2/6/14
$1
28
38
$
61
4025
12/12/14
$151,1
74
$72.68
4027
8/19/06
$71,914
$
34
57
4029
6/5/11
$152,446
$73.29
40
30
7/10/11
$57,727
$27.75
4031
10/20/13
$78,869
$37.92
4034
5/21/06
$90,930
$43.72
45
4037
9/13/13
$67,866
$32.
63
4038
4/14/12
$
64
58
$31.05
4039
5/30/13
$91,
77
$44.12
4044
12/3/15
$
59
$28.47
4045
6/7/16
$32,367
$15.56
4046
9/4/06
$115,974
$
55
54
4055
6/17/18
$99,786
$47.97
4060
2/1/12
$73,6
50
$35.
41
42
4061
2/28/12
$154,933
$74.
49
4064
1/18/16
$144,571
$69.51
4067
10/29/12
$124,996
$60.09
4068
7/15/03
$145,776
$70.08
4070
4/4/17
$80,191
$38.55
4075
10/2/16
$75,053
$36.08
4078
7/15/09
$83,851
$40.31
4082
7/2/15
$82,411
$39.
62
4086
9/18/07
$114,721
$55.15
4088
7/18/17
$108,342
$52.09
4089
10/16/16
$81,050
$38.97
4090
11/15/15
$
87
$42.14
4092
7/7/08
$98,943
$47.57
4093
8/25/10
$93,936
$45.16
4095
12/31/04
$133,678
$64.27
4097
2/26/07
$162,731
$78.24
4104
7/21/08
$71,690
$34.47
4106
5/7/17
$150,263
$72.24
4107
11/5/13
$78,334
$37.66
4118
8/13/17
$74.49
4119
8/31/16
$86,384
$41.53
4120
8/30/13
$127,190
$61.15
4121
8/31/11
$148,111
$71.21
4122
8/4/14
$86,147
$41.42
4126
1
2/24/16
$60,641
$29.15
4128
5/16/03
$126,426
$60.78
4133
5/29/12
$119,1
65
$57.29
4134
6/30/17
$98,007
$47.12
4135
$76,956
$37.00
4137
1/14/09
$98,634
$47.42
4139
2/20/14
$87,056
$41.85
4144
12/4/17
$96,062
$46.18
4
146
12/4/11
$104,961
$50.46
4147
9/30/17
$122,352
$58.82
4150
9/6/17
$33,367
$16.04
4152
7/19/12
$151,523
$72.85
4155
7/16/01
$89,522
$43.04
4163
9/11/14
$74,419
$35.78
4167
8/26/05
$111,536
$53.62
4169
3/14/14
$65,100
$31.30
4175
11/29/11
4176
11/23/17
$135,533
$65.16
4177
3/26/12
$82,515
$39.67
4181
$123,391
$59.32
4183
10/29/14
$65,126
$31.31
4186
3/9/18
$172,291
$82.83
4189
4/24/11
$53,669
$25.80
4191
7/11/04
$71,026
$34.15
4193
10/27/15
$125,004
$60.10
4198
6/5/17
$73,447
$35.31
4199
7/16/12
$151,174
4204
12/14/13
$61,212
$29.43
4205
11/26/14
$106,640
$51.27
4207
6/22/14
$91,205
$43.85
4208
2/15/16
$61,383
$29.51
4212
4/4/19
$61,068
$29.36
4214
5/9/13
4218
11/30/06
$99,130
$47.66
4220
9/17/06
$164,033
$78.86
4221
Malware reverse engineer
$74,000
$35.58
4225
8/1/04
$63,125
$30.35
4232
4/9/13
$86,787
$41.72
4237
11/2/14
$95,957
$46.13
4238
6/24/18
$101,386
$48.74
4239
1/6/17
$78,985
$37.97
4247
11/23/19
$105,069
$50.51
4249
8/17/07
$107,496
$51.68
4252
3/23/16
$97,885
$47.06
4253
11/18/13
$86,377
4257
7/11/03
$104,220
$50.11
4258
1/24/13
$58,540
$28.14
4259
9/4/04
$106,267
$51.09
4260
9/19/15
$88,743
$42.66
4265
6/24/13
$81,042
$38.96
4271
8/5/11
$72,213
$34.72
4272
7/18/14
$78,873
4274
12/8/14
$87,092
$41.87
4278
9/6/10
$90,153
$43.34
4279
11/3/17
$95,220
$45.78
4284
12/16/10
$143,063
$68.78
4285
3/30/11
$80,909
$38.90
4287
2/5/14
$63,777
$30.66
4291
12/25/15
$66,938
$32.18
4296
12/9/07
$150,868
$72.53
4298
8/28/07
$83,
294
$40.05
4299
6/1/11
$76,158
$36.61
4300
7/10/18
$108,866
$52.34
4301
11/7/13
$96,582
$46.43
4302
3/8/17
$87,519
$42.08
4303
1/19/18
$113,246
$54.45
4304
6/1/06
$81,779
$39.32
4305
7/27/16
$78,015
$37.51
4307
8/27/07
$73,807
$35.48
4310
1/21/11
$108,326
$52.08
4311
12/13/15
$92,847
$44.64
4313
11/11/10
$39,808
$19.14
4314
12/28/05
$98,771
$47.49
4316
10/7/17
$
149
$71.86
4319
12/3/13
$63,933
$30.74
4324
6/4/11
$87,409
$42.02
4326
5/3/12
$65,955
$31.71
4327
1/29/12
$68,226
$32.80
4329
6/21/10
$119,537
$57.47
4330
10/14/15
$94,038
$45.21
4332
9/28/04
$91,507
$43.99
4334
12/28/10
$103,736
$49.87
4337
10/11/15
$64,200
$30.87
4342
7/13/11
$156,750
$75.36
4343
12/29/17
$96,327
$46.31
4345
7/4/13
$87,480
$42.06
4346
$100,314
$48.23
4352
7/4/16
$50,377
$24.22
4354
7/17/02
$68,056
$32.72
4355
4/1/07
4359
11/26/06
$76,864
$36.95
4
361
6/10/11
$87,601
$42.12
4368
2/24/18
$79,063
$38.01
4
369
8/31/05
4377
2/12/08
4380
7/1/17
$104,793
$50.38
4381
12/29/11
$112,223
$53.95
4382
4/29/12
$79,591
$38.26
4383
12/16/09
$175,916
$84.58
4385
9/25/08
$74,039
$35.60
4386
7/19/08
4387
8/20/15
$91,444
$43.96
4388
10/16/14
$119,156
4393
9/2/15
$108,058
$51.95
4394
5/6/18
$89,197
$42.88
4395
1/4/18
$71,697
4396
12/10/12
$101,341
$48.72
4397
5/20/13
$84,175
$40.47
4401
8/25/03
$76,305
$36.69
4402
12/7/18
$152,030
$73.09
4405
9/27/12
$54,080
$26.00
4406
6/10/13
$116,075
$55.81
4407
11/20/08
$73,005
$35.10
4409
5/1/12
$112,402
$54.04
4410
6/20/15
$68,222
4411
9/25/14
$95,128
$45.73
4413
12/21/16
$95,622
$45.97
4418
$239,315
$115.06
4419
12/17/06
$70,237
$33.77
4421
2/12/15
$64,201
4423
$102,641
$49.35
4424
2/23/16
$107,153
$51.52
4428
2/6/10
$73,640
$35.40
4429
1/28/10
$68,647
$33.00
4435
6/17/17
$141,110
$67.84
4436
10/5/04
$71,727
$34.48
4438
11/18/09
$54,060
$25.99
4439
2/2/04
$69,656
$33.49
4440
7/21/14
$111,794
$53.75
4441
8/5/12
$80,198
$38.56
4442
11/10/11
$72,536
$34.87
4450
1/12/06
$90,794
$43.65
4455
10/17/08
4457
$102,913
$49.48
4458
12/15/06
4459
5/22/09
$115,580
$55.57
4460
11/28/18
$154,122
$74.10
4461
11/16/05
$75,074
$36.09
4465
10/13/13
$83,367
$40.08
4466
6/2/07
$94,876
$45.61
4467
8/11/14
$43,367
$20.85
4468
1/10/17
$163,045
$78.39
4470
5/17/15
$66,528
$31.98
4471
5/15/18
4472
2/15/11
$74,381
$35.76
4474
9/26/13
$113,023
$54.34
4475
12/12/12
$75,415
$36.26
4479
3/16/11
$68,375
$32.87
4480
1/4/14
$101,709
$48.90
4482
7/20/01
$77,247
$37.14
4484
4/18/18
$111,424
$53.57
4489
3/28/14
$83,075
$39.94
4490
3/11/13
$100,571
$48.35
4497
10/28/12
$68,012
$32.70
4498
$82,319
$39.58
4500
12/5/13
$113,056
$54.35
4507
8/11/16
$55,542
$26.70
4513
2/19/12
$103,721
4515
6/13/09
$89,165
$42.87
4517
7/27/08
$140,865
$67.72
4519
5/29/18
$128,901
$61.97
4520
4/11/04
$179,195
$86.15
4522
12/10/15
$85,442
$41.08
4530
5/1/17
$72,946
$35.07
4532
2/10/16
4535
6/14/06
$110,708
$53.23
4541
12/2/09
$170,954
$82.19
4543
10/20/12
4544
8/15/18
$69,935
$33.62
4554
1/22/18
$43,962
$21.14
4558
1/31/11
$85,256
$40.99
4563
3/16/16
$62,319
$29.96
4564
11/23/12
$88,639
$42.61
4565
6/13/04
$79,584
4566
9/28/01
$87,517
4567
11/6/07
$71,747
$34.49
4571
7/12/11
$75,261
$36.18
4572
10/6/10
$92,079
$44.27
4576
10/30/10
$92,931
$44.68
4580
$186,670
$89.75
4587
6/24/08
$76,499
$36.78
4589
$70,358
$33.83
4591
1/4/16
$109,128
$52.47
4592
10/6/09
$133,138
$64.01
4593
1/20/12
$86,597
$41.63
4594
5/3/14
$78,529
$37.75
4595
11/29/09
$96,566
4597
12/17/15
$158,066
$75.99
4598
$81,287
$39.08
4604
$71,671
$34.46
4611
$132,142
$63.53
4612
3/17/16
$111,196
$53.46
4617
9/20/06
$87,407
4618
6/13/11
$76,031
$36.55
4619
9/30/12
$83,424
$40.11
4620
4/29/11
$178,456
$85.80
4621
12/1/18
$81,730
$39.29
4626
8/19/14
$55,720
$26.79
4630
10/13/07
$61,779
$29.70
4636
7/7/04
$75,293
$36.20
4639
3/12/13
4648
7/7/17
$115,966
$55.75
4653
9/13/12
$91,131
$43.81
4656
4660
9/9/12
$120,986
$58.17
4661
8/29/15
$117,062
$56.28
4665
8/16/13
$115,283
$55.42
4668
5/21/13
4671
1/13/15
$105,637
$50.79
4675
8/10/13
$101,360
$48.73
4677
11/11/14
4680
6/18/09
$84,713
$40.73
4683
5/6/11
$58,294
$28.03
4687
8/25/18
$87,583
$42.11
4690
6/27/12
$82,471
$39.65
4693
10/2/15
$75,920
$36.50
4694
11/16/15
$101,016
$48.57
4695
1/31/15
4696
8/26/17
$128,825
$61.94
4699
10/8/10
$79,542
$38.24
4700
10/7/14
$63,946
4705
8/21/13
$80,045
$38.48
4709
10/4/12
4712
2/25/14
$97,323
$46.79
4713
2/13/14
$86,666
$41.67
4714
8/24/15
$94,700
$45.53
4717
12/19/09
$82,601
$39.71
4719
9/1/06
$98,234
$47.23
4723
10/8/11
$75,270
$36.19
4724
3/8/15
$103,349
$49.69
4726
1/4/05
$134,847
$64.83
4727
9/7/12
$122,391
$58.84
4730
8/31/04
$107,530
$51.70
4731
10/12/12
$83,430
4733
8/9/12
$80,666
$38.78
4734
10/21/16
$87,047
4740
11/1/16
$77,495
$37.26
4742
4/21/08
$90,599
$43.56
4745
3/14/17
$75,144
$36.13
4746
$84,679
$40.71
4748
10/19/12
$75,612
$36.35
4757
10/15/14
$112,994
$54.32
4759
10/11/13
$67,624
$32.51
4761
1/17/15
4766
9/23/15
$84,076
$40.42
4768
5/3/13
$114,251
$54.93
4769
9/15/14
$71,311
$34.28
4771
12/1/13
$159,215
$76.55
4775
$162,030
$77.90
4780
8/2/02
$62,747
$30.17
4782
4/6/19
4784
5/12/12
$102,238
$49.15
4786
8/6/11
4790
6/11/13
4792
$131,698
$63.32
4794
$67,987
$32.69
4798
9/22/13
$119,285
$57.35
4803
10/29/11
$52,064
$25.03
4806
5/4/11
$116,208
$55.87
4809
11/6/10
$99,135
4811
4/22/10
$74,814
$35.97
4813
6/20/08
$127,890
$61.49
4817
7/4/17
$84,270
$40.51
4818
12/29/16
$64,458
$30.99
4820
$69,777
$33.55
4823
8/14/03
$72,005
$34.62
4824
5/17/10
4825
9/5/16
$78,900
$37.93
4826
1/7/12
$64,797
$31.15
4830
8/3/17
$91,748
$44.11
4831
11/23/08
$100,632
$48.38
4834
4/24/19
$100,198
$48.17
4837
$62,836
$30.21
4840
2/1/14
$87,054
4841
1/8/13
$61,121
$29.39
4842
$60,802
$29.23
4843
6/23/16
$86,199
$41.44
4845
5/23/11
$149,466
4846
10/10/13
$87,943
$42.28
4854
11/8/14
4855
4/2/15
$96,338
$46.32
4857
9/2/14
4860
5/5/06
$75,179
$36.14
4864
1/26/18
$69,665
4872
1/19/12
$68,762
$33.06
4876
1/11/17
$139,377
$67.01
4879
7/13/02
$106,600
$51.25
4880
9/13/11
$95,662
$45.99
4882
$81,276
4883
7/31/11
$131,580
$63.26
4885
8/25/02
4897
10/24/07
$108,604
$52.21
4901
6/12/11
4902
9/5/11
$82,016
$39.43
4904
12/19/13
$139,515
$67.07
4905
5/12/18
4906
11/20/10
$186,925
$89.87
4907
2/6/19
$50,421
$24.24
4911
5/29/06
$92,076
4913
6/13/17
$71,851
$34.54
4915
10/25/11
$132,230
$63.57
4918
5/15/11
$143,005
$68.75
4919
1/29/13
$125,367
$60.27
4931
9/1/16
$161,867
$77.82
4932
2/2/14
$128,943
$61.99
4943
12/5/17
$77,443
$37.23
4944
4945
10/13/05
$61,902
$29.76
4946
2/21/15
$72,352
$34.78
4947
6/21/13
$121,455
$58.39
4950
10/18/17
$118,997
$57.21
4953
1/5/16
$114,854
$55.22
4957
3/2/09
$110,877
$53.31
4958
7/17/13
4960
4/10/13
$84,275
$40.52
4961
1/25/05
$117,214
$56.35
4964
10/21/10
$83,911
$40.34
4965
2/27/12
4971
1/24/04
$76,702
$36.88
4972
7/27/07
4981
2/2/10
$117,692
$56.58
4982
$74,512
$35.82
4992
4/20/15
$99,821
$47.99
4998
9/25/10
$75,969
$36.52
Section 2: Complete
Sum
Roles
Acctg/Fin 12 1
African-Am
26.
344
2003
$1,656,872
Admin 3 2 Asian 25
6.7204301075
2004
$47,830,245
Advertising 6 3 Caucasian
216
58.064516129
2005
$84,088,009
CEO 1 4
Hispanic
8.8709677419
2006
$130,427,572
CFO 1
TOTAL
372
2007
$146,938,882
CIO 1
2008
$139,117,818
Controller 18
2009
$143,547,199
COO 1 Gender # %
2010
$144,834,875
Cyber Analyst 146 1
Male
295
79.3010752688
2011
$149,578,842
Cyber Mgr 8 2
Female
20.6989247312
2012
$155,740,613
Cyber Software Engineer 23 TOTAL 372 100
2013
$144,759,828
Eng Mgr 3
2014
$156,714,301
Forensics Analyst 39
2015
$150,201,379
Investigator 8
Education Level
2016
$154,750,829
IT Mgr 2 12
HS
4.8387096774
2017
$158,253,462
IT Staff 18 14
AA
23.3870967742
2018
$156,494,223
Logistics 5 16
BA/BS
203
54.5698924731
2019
$165,800,498
Logistics Mgr 1 19
Masters+
17.2043010753
Malware Reverse Engineer 16 TOTAL 372 100
2021
Marketing 5
2022
Physical Security 18
2023
Public and Business Office Team 14
Marital Status
2024
Public and Business Office Team Mgr 1 1
Married
Quality Assurance 5 2
Single
Sr Cyber Analyst 2 TOTAL 372 100
Sr Cyber Investigator 26
Sr Forensics Mgr 122
Sr Public and Business Office Team Mgr 3
Region Key
TOTAL
508
PA Northeast 149
40.0537634409
IL Midwest 125
33.6021505376
NE C-Plains 98 26.3440860215 NE 98 26.3440860215
TOTAL 372 100 TOTAL 372 100
Section 3: Complete
Descriptive Statistics
Be sure to include the correct units where applicable for the summary statistics below
Frequency
Table by Salary
s
$40.05
Range / Upper Limit
next Tab
$74.49
$16.00
0
$0.27
$0.77
70000
$115.06
$15.56
100000
.00
$372.00 $372.00 $372.00 $372.00
Label Graph on
0
1
Awais Khan March 17,2021 1
Excel Summary Stats
| Section 3: Complete Descriptive Statistics | ||||||||
| Yrs of SVC | ||||||||
| Standard Error | $1,703.33 | $0.82 | $0.22 | $0.52 | ||||
| Standard Deviation | ||||||||
| Sample Variance | ||||||||
| -$0.09 | ||||||||
| Minimum | ||||||||
| Maximum | ||||||||
Graphs-Charts
| Line Graph |
Emplyees by Gender
Male Female 0.793010752688172 0.20698924731182797
Employee by education level
HS AA BA/BS Masters+ 4.8387096774193547E-2 0.23387096774193547 0.54569892473118276 0.17204301075268819
Employees by Marital Status
Married Single 0.72043010752688175 0.27956989247311825
Sales Summary
Sa les Summary (Provided) Yr 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Sales 1656871.8930150992 47830244.546799615 84088009.193400696 130427572.07159656 146938882.11983776 139117817.9909192 143547199.3314777 144834874.89356914 149578841.81593996 155740613.19537732 144759828.34312081 156714300.52984941 150201379.20405364 154750828.73739058 158253462.20716339 156494222.6692971 165800497.95999998
No of Employees By Race
# African-Am Asian Caucasian Hispanic TOTAL 1 2 3 4 98 25 216 33 372 % African-Am Asian Caucasian Hispanic TOTAL 1 2 3 4 26.344086021505376 6.7204301075268811 58.064516129032263 8.870967741935484 100
No of Employees per state
# PA IL NE 149 125 98 % PA IL NE 40.05376344086021 6 33.602150537634408 26.344086021505376
Histogram
| More |
Histogram
Frequency 20000 30000 40000 50000 60000 70000 80000 90000 100000 110000 120000 130000 140000 150000 160000 170000 180000 190000 200000 More 0 0 3 5 12 40 60 58 43 33 30 16 10 18 25 10 6 2 0 1
Bin
Frequency
Sorted Data
| Vested Yr | 12/31/19 | |
| $95,985 | ||
| $128,384 | $61.72 | |
| $34.57 | ||
| $59,219 | ||
| 12/24/16 | ||
| 4369 | ||
| $9,725,922 | C-Plains Total | |
| $44.36 | ||
| $111,801 | ||
| $48.33 | ||
| $125,156 | ||
| 4030 | ||
| $73,650 | $35.41 | |
| $39.62 | ||
| $87,641 | ||
| 4361 | ||
| $12,548,434 | Midwest Total | |
| 11/25/18 | $90,688 | $43.60 |
| $78,475 | $37.73 | |
| $93,518 | ||
| 5/27/04 | ||
| $32.63 | ||
| $64,580 | ||
| $91,771 | ||
| $55.76 | ||
| $119,165 | ||
| 4146 | ||
| $14,803,714 | Northeast Total | |
| Grand Total | ||
| 33.3333333333 | ||
Projected sales
| Forecast(Sales) | Lower Confidence Bound(Sales) | Upper Confidence Bound(Sales) |
| $169,573,508 | $136,658,203 | $202,488,813 |
| $173,361,189 | $120,748,063 | $225,974,314 |
| $177,148,869 | $105,087,463 | $249,210,275 |
| $180,936,550 | $88,785,158 | $273,087,942 |
| $184,724,230 | $71,588,978 | $297,859,483 |
Sales 1656871.8930150992 47830244.546799615 84088009.193400696 130427572.07159656 146938882.11983776 139117817.9909192 143547199.3314777 144834874.89356914 149578841.81593996 155740613.19537732 144759828.34312081 156714300.52984941 150201379.20405364 154750828.73739058 158253462.20716339 156494222.6692971 165800497.95999998 Forecast(Sales) 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 165800497.95999998 169573508.20896068 173361188.7347073 177148869.26045391 180936549.78620052 184724230.31194714 Lower Confidence Bound(Sales) 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 165800497.95999998 136658203.08747235 120748063.17676568 105087463.09731175 88785157.738277659 71588978.118450373 Upper Confidence Bound(Sales) 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 165800497.95999998 202488813.33044901 225974314.29264891 249210275.42359608 273087941.83412337 297859482.50544393
For this Project, you have to follow the instruction given in each steps 1 – 10 below. I have already done the project but end up failing this project. For that reason , I would like you to make corrections on my given attached sheet and give it back to me.However, you have to redo the several steps compelty as well. Like answering questions and essay.
Conduct Quantitative Analysis – Management
Transcript
Your manager, Pat Williams, invites you to meet again to discuss another project. It turns out that Cybertech’s competitors have been closing in on market share. Pat asks you to analyze data about the company’s workforce and to prepare an analysis of its current composition. The report is due in two weeks. Your quantitative analysis will be used to advise the company’s management on the cost of doing business, and how to achieve success and income revenues, as well as make recommendations on the allocation of salaries across the company. Pat explains more about the requirements. Pat asks that your report must consider personnel by organizational roles, salaries, length of service, level of education, age, race, gender, marital status, and region. Pat explains that your analysis will be reviewed to determine how the company’s employee demographics compare with industry peers and competitors. You learn that you will present your report to leadership at their quarterly strategic planning meeting. You know that you’ll need to use your statistical skills and technical skills to identify and manipulate the data. You’ll also need to draw relevant conclusions based on quantitative reasoning. First, sketch out a plan to review your skills in math, statistics, and Excel. Second, you’ll need to work through the data to produce supporting charts and graphs. Third, you’ll need to complete the analysis well before the due date. Time to get busy.
Step 2: Set Up Your Spreadsheet
Now that you’ve assessed and refreshed these important skills, you’re ready to begin. First
download the Excel template
( I have attached spreadsheet already.) and use it to
set up your spreadsheet
. ) I am providing another work sheet that I worked on and end up not getting good grade. So make correction on that sheet.) This step has you set up a basic view in preparation for the use of several tools.
After you’ve formatted and set up the basic view and saved it with your name, you’re ready to move to the next step and
add data
.
Step 3: Add Data
With the spreadsheet set up and saved with your last name, you’re ready to add data. In Section 1 on the Data page, complete each column of the spreadsheet to arrive at the desired calculations.
When you’re ready, move on to the next step, where you will use functions to
summarize the data
.
Add Data
In Section 1 on the Data page, complete each column of the spreadsheet to arrive at the desired calculations. Use Excel formulas to demonstrate that you can perform the calculations in Excel. Remember, a cell address is the combination of a column and a row. For example, C11 refers to Column C, Row 11 in a spreadsheet.
Reminder: Occasionally in Excel, you will create an unintentional circular reference. This means that within a formula in a cell, you directly or indirectly referred to (back to) the cell. For example, while entering a formula in A3, you enter =A1+A2+A3. This is not correct and will result in an error. Excel allows you to remove or allow these references.
Hint: Another helpful feature in Excel is Paste Special. Mastering this feature allows you to copy and paste all elements of a cell, or just select elements like the formula, the value or the formatting.
“Names” are a way to define cells and ranges in your spreadsheet and can be used in formulas. For review and refresh, see the resources for Create Complex Formulas and Work with Functions.
Ready to Begin?
1. To calculate hourly rate, you will use the annual hourly rate already computed in Excel, which is 2080. This is the number most often used in annual salary calculations based on full time, 40 hours per week, 52 weeks per year. In E11 (or the first cell in the Hrly Rate column), create a formula that calculates the hourly rate for each employee by referencing the employee’s salary in Column D, divided by the value of annual hours, 2080. To do this, you will create a simple formula: =D11/2080. Complete the calculations for the remainder of Column E. If you don’t want to do this cell by cell, you can create a new formula that will let you use that same formula all the way to the end of the column. It would look like this: =$D$11:$D$382/2080.
2. In Column F, calculate the number of years worked for each employee by creating a formula that incorporates the date in cell F9 and demonstrates your understanding of relative and absolute cells in Excel. For this, you will need a formula that can compute absolute values to determine years of service. You could do this longhand, but it would take a long time. So, try the YEARFRAC formula, which computes the number of years (and even rounds). Once you start the formula in Excel, the element will appear to guide you. You need to know the “ending” date (F9) and the hiring date (B11). The formula looks like this: =YEARFRAC($F$9,B11), and the $ will repeat the formula calculation down the column as before if you grab the edge of the cell and drag it to the bottom of the column.
3. To determine if an employee is vested or not In Column I, use an IF statement to flag with a “Yes” any employees who have been employed 10 years or more. Here is how an IF statement works: =IF(X is greater (or less than) Y, “Answer”, IF not, “Answer”). To create this as a formula, it would look like this: =IF(F11>=10,”Yes”,”No”). You can drag this formula down the column, or highlight the starting cell, hold down the Shift key, and zip down to cell 382 and release, and the whole column should compute properly.
4. Using the VLookup function, use the Region Key located at F417:G420 to fill in the cells in Column N to identify the region in which the employee is located based on the state listed in Column M. (If this function is new to you— hang in there—this one is worth it.
VLOOKUP requires that you tell Excel where to look for the information. =VLOOKUP(Cell value to look up, From:To, Position, Alternate answer?) Go to the data first:
Snip is used by courtesy of Microsoft.
You will devise a formula that will match the state to a region (in position 2). We will use the $ function to enable a repeat of the formula down the column. =VLOOKUP(M11,$F$417:$G$420,2,FALSE).
To view videos that explain these formulas, refer back to Step 1 under the link titled Access Tutoring Help and Other Resources. The videos were created for another course but pertain to this same data set.
Step 4: Use Functions to
Summarize the Data
With the data built, you are ready to start using tools to summarize the data, using Countif and the Sum function to do the math. In this step, you’ll begin to see patterns in the data and the story of the workforce.
Take a breather here if you need it. You should strive to work through the first four steps this week. Check in with your instructor.
With this step complete, you’re ready to begin your analysis.
Learning Topic
Summarize the Data
You are now ready to move into Section 2 to prepare the data for future analysis, to include simple statistical analyses and charts and graphs to present the data. To start, begin by presenting categories of data in summary tables and counting them, totaling them, and calculating percentages. This basic analysis helps you begin to describe patterns in the data and starts to form the story of the workforce.
Complete each table in Section 2. Use the Countif Function to count each item in each table. Use the Sum Function to total the tables when required. Calculate percentages for each table as required. Format cells appropriately. Remember to make smart use of reference cells in formulas (avoid typing in numbers or text into formulas—point to other cells) and use mixed and fixed cell references to make copying formulas easier/faster. Your supervisor will look for this!
Using the COUNTIF Function
1
The COUNTIF function allows the student to tabulate the instances (or frequency) of a specified value (character or numeric) within a range of cells in Excel. To begin, you select a cell and type:
2
After entering the initial text, it will ask you to select your range and criteria. The range represents your highlighted selection of cells that you are tabulating a specified value. To select your range, you can highlight the cells. When you do that, you’ll see how the function automatically inserts the cell range into your formula (below). When you do that, you can insert a comma (,) after the range (as shown by the circle) and then move to the criteria portion of the formula.
3
Your criteria is the investigate component of the formula. So if the formula is asking for cell values less than 2, it will tabulate all selected cells in your range that are less than 2. In the formula, it would resemble the following: =COUNTIF(A4:A12, <2). Note: In terms of tabulating the frequency of text (such as region), it’s important to note the need to use “ “ to make the variable character (below). When you entered your criteria and are ready to tabulate, you can close your formula by entering a close parenthesis --- ).
Note: If you are dealing with numeric data, the “ “ are not needed before and after the text of your key variable.
Step 5: Analyze the Workforce
You’ve summarized the data. Next, you will employ
descriptive or summary statistics
to analyze the workforce. Your summary tables described “how many.” Now you will
calculate mean, median, and mode for the categories of data, and derive the deviation, variance, and dispersion, and distribution
. This is where it gets interesting.
You will be working in Section 3 of the Data tab in the spreadsheet to complete the descriptive statistics for the five categories (Salary, Hourly Rate, Years of Service, Education, and Age). Using Excel formulas, complete the table.
After you have used Excel formulas to find this information, you will next use the Toolpak to find summary statistics.
Step 6: Use the Analysis Toolpak
Your data set is now built. Now, you will use the same functions to perform the
Descriptive Analysis Using the Analysis Toolpak
. This is a handy feature to know. Remember that there may be some minor differences in the answers depending on the version.
You should now have Tab 2 complete: Excel Summary Stats. Next, you’ll create charts and a histogram for Tabs 3 and 4.
Descriptive Analysis Using the Analysis Toolpak
The steps you just followed enabled you to calculate descriptive statistics using individual Excel functions. Did you know that you can generate the same descriptive statistics in one easy step? 1. First, make sure you have enabled the data analysis toolpak feature. When you completed that successfully, you will see the words “Data Analysis” or an icon on the top right on the Data functions. Select that and then choose “Descriptive Statistics” from the list. 2. The next step will be to provide the input and output. Since you want to have statistics for all the selected categories, you will provide the location of the data on the spreadsheet in the input box. o Provide the inclusive cells for the five categories by typing in the field, or capture the columns with your mouse and the field will show in the input range. o Check the labels box so you have titles for the categories. Then select “New Worksheet Ply.” Your output will be now be in a new sheet on your tab. 3. Label your new sheet Summary Stats and format the columns for readability. 4. Compare your calculations using the data analysis feature to the results you obtained in the previous step, when you calculated the results manually with individual functions. You should not have a large disparity. This tool is handy for quick computations, and you will use it again to create your histogram in Step 7.
Step 7: Create Charts and a Histogram
Where would we be without the ability to view data in charts? It is sometimes easier to grasp the context of data if it is captured in an image. In this step, you will
work with data to create charts
, adding a tab for charts, and another for a histogram.
In this step, you will build Tab 3: Graphs—Charts and Tab 4: Histogram. After you complete these tabs, you’ll be ready to sort the data.
Work With Data to Create Charts
It is often helpful to view and interpret analytical results when they are presented visually. Graphs and charts help readers digest and interpret information quickly, consistent with the familiar adage “a picture is worth a thousand words.” Let’s see what we can see in your data analysis.
Create the following graphs in your workbook on a separate tab named Graphs_Charts:
1. Create separate pie charts that show percentages of employees by (1) gender, (2) education level, and (3) marital status. Explore pie chart formats.
2. Create separate bar charts that show the (1) number of employees by race and (2) the number of employee per state.
3. Create a line graph for the sales summary provided.
4. Create a histogram that shows the number of employees in incremental salary ranges of $10,000. Here, you want to show how many employees are making $0–$20,000; $20,001–$30,000; $30,001–$40,000; and so forth, up to the highest salary range. This involves counting how many employees are in each “salary bucket” to create a frequency distribution table and histogram. Histograms seem hard, but mastering how to visualize the frequency of events is helpful for analysis.
Used with permission from Microsoft.
Note: Your Excel spreadsheet template has the upper limit and labels already identified. Complete the table and histogram by engaging the Data Analysis Toolpak. Place the output on a new worksheet and label it Histogram.
Step 8: Copy and Sort the Data
You’ve accomplished a lot with the data set, summary stats, charts, and histograms. Another skill you’ll need to be able to do is sorting data in an Excel worksheet for reporting purposes. You’ll
copy the data so that you can learn how to sort it
. This is a good skill that applies to any Excel application.
In this step, you will create Tab 5: Sorted Data. When you’re finished, you’ll be ready to conduct a quantitative analysis.
See below for example of a sorted spreadsheet.
Copy the Data So That You Can Learn How to Sort It
Many times we want to sort data on an Excel worksheet for reporting purposes. Let’s see what other perspectives the functions of sorting and subtotaling yield.
1. Begin by following the steps in the “How to Copy Excel 2010 Sheet to Another Sheet” provided below. This will allow you to retain your work for Steps 2 through 7. Place the sheet at the end of the workbook and title the tab “Sorted Data.”
2. Delete all rows containing Section 2 and Section 3 work. Be sure to leave the section in cells F417:I422, as this section is referenced for the Vlookup function populating the region; otherwise, you will get a #N/A or #REF! Error in the column for region.
3. Apply the ability to sort data on each column of the spreadsheet, so that you can sort by employee #, hire date, role, etc.
4. Experiment with the filter funnel, sorting the data by various columns. For example, try sorting by employee number from smallest to largest. Try sorting by role in ascending order (A-Z).
5. Sort the spreadsheet by region.
6. Employ the subtotal feature to subtotal the salary for each region, with a grand total for the company.
7. Format the entire spreadsheet to print, so that the columns fit on the pages, and Row 1 repeats on each page.
Step 9: Conduct Quantitative Analysis
In this step, your hard work bears fruit. What does it all mean? Think back to your boss’s reasons for tasking you with this project. Bring your powers of analysis to bear to determine what the data may be telling you. Apply your quantitative reasoning skills to answer five questions that demonstrate your interpretation of the data. The questions are located on the QR Questions_Responses tab in your workbook.
After answering the five questions, finish the project by writing a short essay. The essay will include:
· a one-paragraph narrative summary of your findings, describing patterns of interest
· an explanation of the potential relevance of such patterns
· a description of how you would investigate further to determine if your results could be perceived as good or bad for the company.
Prepare your responses in your workbook on the QR Questions_Responses tab.
Good job! In the next step, you’ll submit the workbook and analysis.
Step 10: Submit Your Completed Workbook and Analysis
You’re now ready to submit the workbook and analysis for review and feedback. Review the requirements for the final deliverable to be sure you have:
1. Excel Workbook with Six Tabs
· Tab 1: Data – completed data sheet (Steps 1–6 above)
· Tab 2: Excel Summary Stats (Step 6)
· Tab 3: Graphs – Charts (Step 7)
· Tab 4: Histogram (Step 7)
· Tab 5: Sorted Data (Step 8)
· Quantitative Analysis
(Step 9; see detail below and move to first position upon completion.)
2. Quantitative Analysis: Answers to Questions and Short Essay
· Prepare your response in this workbook. Create a tab for Quantitative Analysis, create a text box, and paste your answers to the questions in it. Move the Quantitative Analysis tab to the first tab position.
· Your final workbook tabs:
· Quantitative Analysis
· Data
· Excel Summary Stats
· Graphs–Charts
· Histogram
· Sorted Data
3. Format to Be Printed
· Format this workbook so that all the spreadsheets can be printed.
Professor Feedback is listed below, Plus, on that Excel Spread sheet Typed in in RED color as well.
Most of the issues were corrected. However, your formulas for the job titles in Section 2 of the DATA sheet are incorrect. Based on these formulas, there are 508 employees in the company but we know that there are 372. Take a look at your formulas and fix them. Use the formulas you have for the other section 2 tables for guidance. You did those correctly.
No update. First, your essay begins by looking at Sales, but you have no data on the market or demand, so you have no data with which to analyze sales. Then, your second paragraph switches from sales and instead addresses diversity. Paragraph 2 is supposed to tell management why they should care about the pattern you identified in paragraph 1. See my comments in the FEEDBACK File
No update. Answers to the questions are still incorrect and incomplete. Issues with the mathematical operations in support of the essay. See feedback in the attached file