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

With the help of the Chi Square test of independence between the variable of marital status and the variables of smoking habits and source of stress we observe that there is marital status and we expect to have different values ​​in whether the research participants smoke as well as to their main source of stress.

Non parametric correlation

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.

A minimal effect of Gender on the causes of anxiety was also observed.

Two Way ANOVA

Results

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 Tukey’s post hoc analysis showed that among other things differences were observed between widows and couples who have a stable relationship.

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).

3-way ANOVA

Further examination of the Gender factor in the previous relationship showed that it exhibits statistically significant interactions.

Further graphical examination of our factor showed that no interactions occurred in men while the previous transition we described held true in women.

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.