Space

 ***Doctorate Level Questions*** No Plagiarism….Paraphrase the content, and provide Citations and References for each source provided….Please provide a substantive response for EACH question. Each question should each have a word count of 150 words or more….Please provide appropriate foundational knowledge, be factual, and enhance the dialogue….Please do not recite the same words just to provide word count….  

Question One

From the bibliography of your proposed dissertation study, select a peer-reviewed journal article that was done with a quantitative methodology. Cite the article and summarize the study in one paragraph. Then categorize it according to each of the following dimensions:

• Experimental, quasi-experimental, or non-experimental
• Descriptive, predictive, or explanatory
• Retrospective, cross-sectional, or longitudinal

Why did you categorize the article as you did? Do articles in your field of interest commonly fall into this category? Why or why not?

Question Two

What are the primary factors that make it more challenging to conduct experimental studies in the field of education or leadership? Why are these significant? How do these factors affect your own research design for the dissertation study? 

6

MODULE 2

Module 2 Problem Set

EXAMPLE

Grand Canyon University: RES-866

Approaches to Research Design and Data Analysis

May

1

5, 2019

Running head: ASSIGNMENT TITLE HERE

1

Running head: MODULE 2

Introduction

Understanding and interpreting data is a vital component to a learner’s research as it reflects the study results. Properly analyzing the data is also crucial as this portrays the outcomes and delivers research findings which is the purpose of completing the study initially. Once data is extracted and analyzed, further development of the topic is discussed and shared allowing for a deeper sense of knowledge of the included variable, perceptions, and anything discovered throughout the study. Astroth and Chung (2018) discussed the importance of reviewing quantitative research studies highlighting the importance of ensuring the results are presenting and interpreted correctly. This article is geared towards nurses as they utilize evidence-based practices throughout many health care settings therefore properly analyzing data and accurately reporting results is critical in the potential care provided. For the purpose of this paper, the learner completed the assigned tasks of Module 2 Problem set which is provided below.

Drinks | Learning Activity 2.11

1. Create standardized scores for all scale variables (price through alcohol).

[DataSet1] \\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Price per 6-pack

35

1.59

7.19

3.0274

1.12343

Cost per 12 Fluid Ounces

35

.27

1.20

.5057

.18732

Calories per 12 Fluid Ounces

35

68

175

139.77

24.447

Sodium per 12 Fluid Ounces in mg

35

6

27

14.66

6.145

Alcohol by Volume (in %)

35

2.30

5.50

4.5771

.60298

Valid N (listwise)

35

a.

Which beverages have positive standardized scores on every variable?

· The beverages including each variable with positive standardized scores includes UA, UH, UL, UR, and SA.

b.

What does this mean?

· Based on the raw data, these beverages are at or above the mean average or group mean

2. (a) What is the most extreme z-score on each variable? (b) What is the most extreme z-score across all variables?

a.

Variable

Product

Z-Score

price

SA

3.70524

cost

SA

3.70636

calories

UNR

-2.93581

sodium

PF & PJ

2.00859

alcohol

UNR

-3.77651

b.

cost

SA

3.70636

3. What beverage is most typical of all beverages, that is, has z-score values closest to 0 for these variables?

a. The most common beverage is UIR having the closest z-score value to 0.

4. (a) If the variable is normally distributed, what percentage of cases should be above 1 standard deviation from the mean or below 1 standard deviation from the mean?

a. 68%

(b) Calculate this percentage for a couple of the variables. Is the percentage of beverages with an absolute z-score above 1 close to the theoretical value?

b. Upon running calculations for some of the variables, the percentages were above 1 with an absolute z-score and close to the theoretical value.

Notes

Output Created

14-MAY-2019 17:05:54

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav

Active Dataset

DataSet1

File Label

SPSS/PC+

Filter

Weight

Split File

N of Rows in Working Data File

35

Missing Value Handling

Definition of Missing

User defined missing values are treated as missing.

Cases Used

All non-missing data are used.

Syntax

DESCRIPTIVES VARIABLES=price cost calories sodium alcohol
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.

Resources

Processor Time

00:00:00.00

Elapsed Time

00:00:00.25

Variables Created or Modified

ZzZz01

Zscore(price) Price per 6-pack

ZzZz02

Zscore(cost) Cost per 12 Fluid Ounces

ZzZz03

Zscore(calories) Calories per 12 Fluid Ounces

ZzZz04

Zscore(sodium) Sodium per 12 Fluid Ounces in mg

ZzZz05

Zscore(alcohol) Alcohol by Volume (in %)

Census | Learning Activity 3.9

1. Run the Frequencies procedure on the following variables: sex, wrkstat (Labor Force Status), paeduc (Father’s highest degree), and satjob (Job or Housework).

a. What is the scale of measurement for each?

· Sex – nominal

· Work stat – nominal

· Sat job – nominal

· Par educ – scale

b. Request appropriate summary statistics and charts.

Statistics

RESPONDENTS SEX

LABOR FRCE STATUS

FATHERS HIGHEST DEGREE

JOB OR HOUSEWORK

N

Valid

2023

2021

1553

1536

Missing

0

2

470

487

Median

2.00

2.00

1.00

1.00

Mode

2

1

1

1

RESPONDENTS SEX

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

MALE

929

45.9

45.9

45.9

FEMALE

1094

54.1

54.1

100.0

Total

2023

100.0

100.0

LABOR FRCE STATUS

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

WORKING FULLTIME

1003

49.6

49.6

49.6

WORKING PARTTIME

211

10.4

10.4

60.1

TEMP NOT WORKING

53

2.6

2.6

62.7

UNEMPL, LAID OFF

74

3.7

3.7

66.4

RETIRED

336

16.6

16.6

83.0

SCHOOL

57

2.8

2.8

85.8

KEEPING HOUSE

227

11.2

11.2

97.0

OTHER

60

3.0

3.0

100.0

Total

2021

99.9

100.0

Missing

NA

2

.1

Total

2023

100.0

FATHERS HIGHEST DEGREE

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

LT HIGH SCHOOL

538

26.6

34.6

34.6

HIGH SCHOOL

679

33.6

43.7

78.4

JUNIOR COLLEGE

38

1.9

2.4

80.8

BACHELOR

187

9.2

12.0

92.9

GRADUATE

111

5.5

7.1

100.0

Total

1553

76.8

100.0

Missing

IAP

354

17.5

DK

109

5.4

NA

7

.3

Total

470

23.2

Total

2023

100.0

JOB OR HOUSEWORK

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

VERY SATISFIED

778

38.5

50.7

50.7

MOD. SATISFIED

570

28.2

37.1

87.8

A LITTLE DISSAT

135

6.7

8.8

96.5

VERY DISSATISFIED

53

2.6

3.5

100.0

Total

1536

75.9

100.0

Missing

IAP

453

22.4

DK

19

.9

NA

15

.7

Total

487

24.1

Total

2023

100.0

Bar Chart

2. (a) For which of these variables is it appropriate to use the median? (b) What conclusions can you draw about the distributions of these variables?

a. The variables for which it is most appropriate to use the median are high school education (paeduc) and Job or Housework (satjob) as these measurements are best for this category.

b. The conclusions that can be drawn include that with more education, the higher propensity of having full time employment. More than half reported being satisfied with their employment and more than half did not attend college.

3. (a)What percent of respondents have a bachelor’s degree, or higher? (b)What percent of respondents are working?

a. 14.7% of respondents have a bachelor’s degree or higher

b. 60% of respondents are working either full time or part time

4. How might you combine some of the categories of wrkstat to ensure that there are a sufficient number of respondents in each category?

a. Completing a summary analysis could lend support in determining grouping availability however some of categories that could ensure a sufficient amount of respondents could be employed, retired, and keeping house as they represent cross-categories with high percentages to fulfill the gap.

FREQUENCIES VARIABLES=sex wrkstat padeg satjob

/STATISTICS=MEDIAN MODE

/BARCHART FREQ

/ORDER=ANALYSIS.

Frequencies

Notes

Output Created

14-MAY-2019 16:59:13

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Census.sav

Active Dataset

DataSet2

Filter

Weight

Split File

N of Rows in Working Data File

2023

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.

Resources

Processor Time

00:00:02.06

Elapsed Time

00:00:01.31

Drinks | Learning Activity 4.18

1. Run Frequencies on the variable alcohol, requesting the summary statistics median and mean, plus a histogram with a superimposed normal curve. Suppress the display of the frequency table.

Statistics

Alcohol by Volume (in %)

N

Valid

35

Missing

0

Mean

4.5771

Median

4.7000

2. (a) What is the value of value of alcohol that splits the distribution in half? (b) Is the median the same as the mean? (c) Which value is lower? (d) What does that tell you about the shape of the distribution of alcohol?

a. 4.7 splits the distribution in half

b. The mean and median are not the same as the mean is 4.5771 and the median is 4.7

c. The mean of 4.5771 is lower than the median of 4.7

d. The data is skewed negatively which is indicated by the longer tail

3. (a) Does the histogram verify your description of the distribution of alcohol? (b) How does it differ from a normal distribution?

a. Yes, as it does support being it shows a negative distribution on the left versus a positive distribution on the right which presents alignment

b. Normal distribution is centered and symmetrical which is not apparent as it is skewed left presenting a negative distribution.

4. Run Descriptives to obtain default statistics for price and calories. (a) On which variable is there more dispersion? (b) Is it even realistic to compare these two variables since they are on different scales?

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Price per 6-pack

35

1.59

7.19

3.0274

1.12343

Calories per 12 Fluid Ounces

35

68

175

139.77

24.447

Valid N (listwise)

35

a. There is more dispersion with Calories per 12 Fluid Ounces

b. It is not logical to compare these variables being they are on different scales

5. Continuing your analysis of price and calories, run the Explore procedure for these two variables. Request a histogram in addition to the defaults.

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

Price per 6-pack

35

100.0%

0

0.0%

35

100.0%

Calories per 12 Fluid Ounces

35

100.0%

0

0.0%

35

100.0%

Price per 6-pack

Calories per 12 Fluid Ounces

Calories per 12 Fluid Ounces

1. Does the standard error of each variable help you better determine which variable has more dispersion?

a. There is a lack of accuracy therefore it does not better identify which has more dispersion

2. Review the boxplots and histogram for each variable. (a) Which one has more outliers? (b) What are the outliers on each? (c) Which variable now appears to have more dispersion, based on these graphs? (d) Does that match what you expected based on the statistics?

a. Calories per 12 Fluid Ounces is the variable with the highest outliers

b. The outliers are 2 and 6 for Calories per 12 Fluid Ounces

c. The most dispersion is Price per pack after the outliers are removed

d. Yes, this does match my expectations

Price per 6-pack Stem-and-Leaf Plot

Frequency Stem & Leaf

4.00 1 . 5677

6.00 2 . 122344

15.00 2 . 555555666777899

2.00 3 . 13

1.00 3 . 6

2.00 4 . 23

5.00 Extremes (>=4.6)

Stem width: 1.00

Each leaf: 1 case(s)

Calories per 12 Fluid Ounces Stem-and-Leaf Plot

Frequency Stem & Leaf

6.00 Extremes (=<113)

.00 13 .

2.00 13 . 56

6.00 14 . 044444

9.00 14 . 555779999

7.00 15 . 0122344

2.00 15 . 57

1.00 16 . 2

2.00 Extremes (>=170)

Stem width: 10

Each leaf: 1 case(s)

FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.

Frequencies

Notes

Output Created

14-MAY-2019 16:59:13

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Census.sav

Active Dataset

DataSet2

Filter

Weight

Split File

N of Rows in Working Data File

2023

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=sex wrkstat padeg satjob
/STATISTICS=MEDIAN MODE
/BARCHART FREQ
/ORDER=ANALYSIS.

Resources

Processor Time

00:00:02.06

Elapsed Time

00:00:01.31

Frequencies

Notes

Output Created

14-MAY-2019 17:11:58

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav

Active Dataset

DataSet1

File Label

SPSS/PC+

Filter

Weight

Split File

N of Rows in Working Data File

35

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=alcohol
/STATISTICS=MEAN MEDIAN
/HISTOGRAM NORMAL
/FORMAT=LIMIT(10)
/ORDER=ANALYSIS.

Resources

Processor Time

00:00:00.28

Elapsed Time

00:00:00.33

Descriptives

Notes

Output Created

14-MAY-2019 17:13:38

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav

Active Dataset

DataSet1

File Label

SPSS/PC+

Filter

Weight

Split File

N of Rows in Working Data File

35

Missing Value Handling

Definition of Missing

User defined missing values are treated as missing.

Cases Used

All non-missing data are used.

Syntax

DESCRIPTIVES VARIABLES=price calories
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.27

Variables Created or Modified

ZqZq01

Zscore(price) Price per 6-pack

ZqZq02

Zscore(calories) Calories per 12 Fluid Ounces

Explore

Notes

Output Created

14-MAY-2019 17:16:56

Comments

Input

Data

\\Client\C$\Users\lauren.hazeltine\Downloads\Drinks.sav

Active Dataset

DataSet1

File Label

SPSS/PC+

Filter

Weight

Split File

N of Rows in Working Data File

35

Missing Value Handling

Definition of Missing

User-defined missing values for dependent variables are treated as missing.

Cases Used

Statistics are based on cases with no missing values for any dependent variable or factor used.

Syntax

EXAMINE VARIABLES=price calories
/PLOT BOXPLOT STEMLEAF HISTOGRAM
/COMPARE GROUPS
/STATISTICS DESCRIPTIVES
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.

Resources

Processor Time

00:00:00.88

Elapsed Time

00:00:00.86

Conclusion

This module has provided an opportunity for the learner to display proper use of SPSS, data manipulation, and data analysis over a course of exercises. There was much to be explored in properly understanding and interpreting the information. In following the steps to produce the guided results, the opportunity to produce charts and validate data was included. As shared, the ability to produce valid data is only a portion of the purpose research as being able to understand and provide generalization is just as important which has been portrayed. The continued analysis of the problem sets provided a solid foundation for upcoming doctoral research.

References

American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: Author.

Astroth, K. S., & Chung, S. Y. (2018). Focusing on the Fundamentals: Reading Quantitative Research with a Critical Eye. Nephrology Nursing Journal, 45(3), 283. Retrieved from

https://search-ebscohost-com.lopes.idm.oclc.org/login.aspx?direct=true&db=edswss&AN=000437552000008&site=eds-live&scope=site

SPSS (2010) Introduction to statistical analysis using IBM SPSS Statistics student guide retrieved form: RES866.7P5CL_introduction_to_statistical_analysis_using_ibm_spss_statistics