SPSS PRACTICE: SETTING UP A DATA SET

Please complete the following in SPSS and answer questions.

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SPSS Practice: Setting Up a Data Set

Context

To best prepare for the upcoming assignments, you should thoroughly familiarize yourself with the basic operations of SPSS

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In addition to the unit’s SPSS-based reading, media, and resources, we strongly encourage you to explore the Internet for complementary explanations. Like learning a foreign language, the trick to retaining a new concept, word, or practical skill is to see how it is used in various contexts. The same is true for the terminology you will encounter in this course. If you look beyond this course to see how others use new SPSS terms, concepts, and functions, it will help you retain the information.

Instructions

For this discussion, you will be practicing data entry. We made the task a bit easier by linking a basic data set in

Resources

, the Emotional Well-Being (SF-36) Study. Refer to the additional helpful links in Resources as you prepare your post, and remember to follow the guidelines in the Faculty Expectations message (FEM).

Your objective is to simply perform data import from an Excel data file to SPSS (as this is often how you will obtain data from non-researchers). First, upload the Emotional Well-Being data setlinked in Resources (note this is an Excel file, so you will need to convert it for use in SPSS). Hint: Select the appropriate scale for each variable.

· Identifying data levels.Data sets may have many different levels of data. The skill you will practice is learning to quickly look through labels in a data view and know immediately what type of data level you are looking at.

· Run frequencies in SPSS. Frequencies are run on all levels of variables. Running frequencies helps youto identify problems with missing or out of range values for your variables. Frequencies will provide you with tables and pie charts to help you analyze the data.

· Run the Explore module.The Explore module is run on the scale (interval or ratio) level data and the ordinal level data. It presents all the information you need to make decisions about ordinal and above level data (for example, 95% CI of the mean). Because of the way Explore works, it is less helpful with nominal data.

Be sure to save a copy of this newly created SPSS data set titled Emotional_Well-Being_(your initials) to the file folder you created for your SPSS work. You willuse this data set againin later units.

Complete the following for your initial post:

1. What did you use for your variables (nominal, ordinal, interval, ratio)?

1. What were the measures of central tendency?Standard deviation?Minimum?Maximum?

1. Describe one or two of the challenges you found while performing these exercises and how you resolved the issues. Where appropriate, provide the address of any website that helped you.

Response Guidelines

Read and respond to the posts of your peers according to the guidelines in the FEM.

Address one or more of the following:

. How do thereported challenges and resolutions of your peers compare to yours?

. Do you have any suggestions that could help your peers?

Resources

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Discussion Participation Scoring Guide

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Emotional Well-Being (SF-36) Study Data Set [XLSX]

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2

>Sheet2

=F)

1.

%

.

1%

0

.00%

		Row Labels		Count of	Gender (0=M,																		1
																																						Female			5																																			3		9
																																				Male			4	8	6
		Grand Total						10

Percentage Totals

Total Female Male 0.5

13 88

8888888888

84

0.

48

6

11

11111111111

Sheet3

Row Labels Count of Gender (0=M, 1=F)
Female

51

.

39

%
Male 48.

61

%
Grand Total

100

.00%

Total Female Male 0.51

38

8888888888884 0.4861111111111111

Sheet5

Row Labels

–

%

-38

–

15%

–

–

8

19%

-88

Grand Total 100.00%

Count of	Age (yrs)
		19				28				15
					29	10%
39-48	13%
			49				58
		59						68		19%
	69		7
						79	8%

Study population age groups

(percentage of total)

Total 19-28 29-38 39-48 49-58 59-68 69-

78

79-88 0.15

27 77

77777777779 9.7

22

22222222222

24

E-2 0.

12

5 0.1

52

77777777777779 0.19

44

44444444444

45

0.19444444444444445 8.

33

33333333333

32

9E-2

Sheet1

Age (yrs) Gender (0=M, 1=F)

Well-Being Score

1 45 Male 1 27

2

Male 3 36

45

3

Female 2

Standard 58

4 39 Female 3 32 Standard

5 79 Female 1

Vegetarian

77

6 27 Male 3 24 Vegetarian 58 100
7 78 Male 1 24 Vegetarian 62 58
8

Male 3 43 Standard 28

9 66 Female 3

Vegetarian 13

10

Female 1 32 Standard

56

11 51 Male 3 33 Vegetarian

77

12 71 Female 1 22 Standard

13

Female 2 43 Standard 55 68

59 Female 3 29 Vegetarian 79

15 68 Male 1 27 Vegetarian 44 40

79 Female 1 36 Vegetarian 15

36 Male 1

Standard 79

Female 2 26 Standard 62 49

19 33 Male 1 29 Standard 68

78 Male 1 26 Vegetarian 82 79

21 43 Female 3

Vegetarian 44 71

22 65 Female 3 39 Standard 36

84 Female 3

Standard 52 66

24 37 Female 3 26 Standard 48

75 Female 3 43 Standard 74 65

26 51 Male 3 23 Standard 23 78
27

Male 3 40 Vegetarian 30 65

28 51 Male 2 26 Vegetarian 80 74
29 23 Male 1 41 Vegetarian 55 71
30 66 Female 2 39 Vegetarian

78

31 45 Female 2 26 Standard 12 88
32

Male 3 43 Standard 56 60

33 70 Male 3 26 Standard 61 75

40 Male 2 41 Standard 63 88

35

Female 3 26 Vegetarian

93

36 26 Female 2 41 Standard 64 60
37 68 Female 3 30 Vegetarian 35 80
38 46 Male 3 35 Standard 62 70
39 77 Male 1 42 Standard 43 43
40 84 Female 3 23 Standard 42 79
41

Female 3 41 Standard 64 50

42 77 Male 3 43 Standard 7 56
43 43 Female 2 36 Standard 31 74
44 27 Female 3 31 Standard 45 41
45 64 Female 3 27 Vegetarian 9 62
46 83 Male 3 33 Standard 11 45

29 Male 2 24 Vegetarian 28 41

48 75 Female 2 32 Vegetarian 35 56
49 77 Male 3 29 Standard 68 71
50 75 Female 1 38 Vegetarian 65

51

Female 1 37 Vegetarian 48 78

52 61 Female 2 26 Standard

87

64 Male 3 24 Standard 24 96

54 63 Female 3 40 Vegetarian 48 56
55 23 Male 3 39 Standard 43 80
56 77 Male 2 37 Standard 22

57 83 Male 2 42 Standard 46 85
58 55 Male 3 22 Standard 21 78
59 21 Female 2 37 Standard 49 42
60 19 Male 2 36 Standard 53 75
61 36 Male 2 32 Standard 42 100
62 52 Male 2 34 Standard 78 93
63 63 Female 3 40 Vegetarian 57 52
64 52 Female 1 25 Standard 46 95
65 34 Male 2 32 Vegetarian 43 91
66 26 Female 3 36 Standard 10 51

62 Male 1 37 Standard 21 52

68 39 Male 3 22 Vegetarian 22 99
69 27 Female 1 27 Vegetarian 75 96
70 60 Male 2 37 Vegetarian 28 71
71 37 Female 3 33 Standard 67 56
72 57 Female 2 36 Standard 40 93

Patient No	Race (1=AA, 2=C, 3=H)	BMI	Dietary treatment (1=Std, 2=veg)	Basline SF-										36	Post-Tx Well-Being
																																											Standard						65					66
				55																												Vegetarian							71
											26					35		87
			80		95
												43							62
				60								40
			30			83
						75								56
			74
		96		99
			57
14							42
16				93
17				31		82
18					21
98
20
							41
					64
					23									37
	72
	25
				46
				63
			70
		34
	54	92
		50
47
	91
73
	85
	53
90
	67