Analysis with SPSS/PSSP/JASP

Analysis with SPSS/PSPP/JASP

Analysis with SPSS

Why use SPSS? SPSSSPSS statstical software SPSS is one of the most widespread statistical programs and provides automated processes with the help of a very detailed graphical interface and a large number of their configuration. In addition it provides the option of writing code with its help Syntax  to speed up repetitive processes.

 

The following is a typical example of Statistical Data Analysis

Sample description

 

From the composite bar graph of percentages on the whole we observe that

1. Work is the most important stressor in all categories of marital status

2. The general concern for the evolution of life concerns mainly the single, those who got married for the first time and those who live with their parents.

3. The marital status that covers the widest range of sources of stress was presented to single people and married people for the first time.

 

Chi Square Test2

Με την βοήθεια του Χ2 Independence test between the marital status variable and the variable smoking habits and source of stress. We observe that there is a marital status.

 

 

Chi-Square Tests

Value

df

AsymptoticSignificance (2-sided)

Pearson Chi-Square

19,059a

7

,008

Likelihood Ratio

18,338

7

,011

Linear-by-Linear Association

,829

1

,363

N of Valid Cases

436

a. 3 cells (18,8%) have expected count less than 5. The minimum expected count is 1,36.

 

 

Chi-Square Tests

Value

df

AsymptoticSignificance (2-sided)

Pearson Chi-Square

112,174a

56

,000

Likelihood Ratio

119,829

56

,000

Linear-by-Linear Association

4,930

1

,026

N of Valid Cases

422

a. 53 cells (73,6%) have expected count less than 5. The minimum expected count is ,20.

 

 

Μη παραμετρικές συσχετίσεις

To control the degree of the relationship between the previous variables, a correlation was performed Spearman and the results showed that the main source of stress is to a small extent influenced by the marital status while the smoking habits are not related to the marital status of the respondent.

 

 

Correlations

marital status

smoker

Spearman’s rho marital status Correlation Coefficient

1,000

,073

Sig. (2-tailed)

.

,128

N

439

436

smoker Correlation Coefficient

,073

1,000

Sig. (2-tailed)

,128

.

N

436

436

 

 

 

Correlations

marital status

source of stress

Spearman’s rho marital status Correlation Coefficient

1,000

,156**

Sig. (2-tailed)

.

,001

N

439

422

source of stress Correlation Coefficient

,156**

1,000

Sig. (2-tailed)

,001

.

N

422

422

**. Correlation is significant at the 0.01 level (2-tailed).

 

Επίσης παρατηρήθηκε και ελάχιστη επίδραση του Φύλου στις αιτίες άγχους.

 

Correlations

sex

source of stress

Spearman’s rho sex Correlation Coefficient

1,000

,099*

Sig. (2-tailed)

.

,043

N

439

422

source of stress Correlation Coefficient

,099*

1,000

Sig. (2-tailed)

,043

.

N

422

422

*. Correlation is significant at the 0.05 level (2-tailed).

 

 

 

Two Way ANOVA

Results

 

Tests of Between-Subjects Effects

Dependent Variable:   Total negative affect 
Source

Type III Sum of Squares

df

Mean Square

F

Sig.

Corrected Model

1470,276a

15

98,018

2,019

,013

Intercept

43267,124

1

43267,124

891,107

,000

marital

658,796

7

94,114

1,938

,062

smoke

32,762

1

32,762

,675

,412

marital * smoke

366,101

7

52,300

0,03

,000

Error

20198,610

416

48,554

Total

184109,000

432

Corrected Total

21668,887

431

a. R Squared = ,068 (Adjusted R Squared = ,034)

 

We observe that the interaction between marital status factors and smoking are statistically significant in 0.001 p-level

Further examination of the differences with its help Tukeys post hoc analysis showed that among other things differences were observed between widows and couples who have a stable relationship.

 

Total negative affect

Tukey HSDa,b,c
marital status

N

Subset

1

2

WIDOWED

7

13,14

MARRIED FIRST TIME

186

18,35

18,35

REMARRIED

30

19,10

19,10

DIVORCED

23

19,43

19,43

LIVING WITH PARTNER

36

19,56

19,56

SINGLE

103

20,20

STEADY RELATIONSHIP

37

22,24

SEPARATED

10

24,40

Sig.

,066

,102

Means for groups in homogeneous subsets are displayed.

 Based on observed means.

 The error term is Mean Square(Error) = 48,554.

a. Uses Harmonic Mean Sample Size = 20,536.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed.
c. Alpha = 0,05.

 

 

Graph of Interactions

Smoking habits have been shown to affect the values of the rating of negative effects during the transition from an informal relationship to a more formal one (marriage).

 

Ανάλυση διασποράς με τρείς παράγοντες

Η επιπλέον εξέταση του παράγοντα Φύλο στην προηγούμενη σχέση έδειξε ότι παρουσιάζει στατιστικά σημαντικές αλληλεπιδράσεις.

 

Tests of Between-Subjects Effects

Dependent Variable:   Total negative affect 
Source

Type III Sum of Squares

df

Mean Square

F

Sig.

Corrected Model

2246,559a

28

80,234

1,665

,020

Intercept

44247,737

1

44247,737

918,110

,000

marital

728,713

7

104,102

2,160

,037

smoke

21,755

1

21,755

,451

,502

sex

35,130

1

35,130

,729

,394

marital * smoke

449,449

7

64,207

1,332

,233

marital * sex

347,783

6

57,964

1,203

,304

smoke * sex

79,565

1

79,565

1,651

,200

marital * smoke * sex

75,414

5

15,083

,002

,000

Error

19422,328

403

48,194

Total

184109,000

432

Corrected Total

21668,887

431

a. R Squared = ,104 (Adjusted R Squared = ,041)

 

Η περαιτέρω γραφική εξέταση του παράγοντα μας έδειξε ότι δεν παρουσιάστηκαν αλληλεπιδράσεις στους άνδρες ενώ η προηγούμενη μετάβαση που περιγράψαμε ισχύει στις γυναίκες.

 

 

Conclusion

The difference in the scores of the negative effects during the transition from the free state or the state of informal cohabitation applies only to women.

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