Writing up the results section of your dissertation.
I can effectively write results if the interaction effect is insignificant. However, in the case where my interaction effect is significant, my simple main effects are so long to write out. e.g.
Just fill in the blanks by using the SPSS output Let’s start by filing in the Mean and Standard Deviation for each condition. Now we’ll finish up by filling in the values related to the T-Test. Here we enter the degrees of freedom (df), the t-value (t), and the Sig. (2-tailed) value (often referred to as the p value).
We’re now ready to set up some of the options for the repeated-measures ANOVA. Click on the Options button. Options. What you see here depends on the version of SPSS you’re using. The most recent version of SPSS (26) has an options dialog box that looks like this. Previous versions include an option for specifying estimated marginal means.
The Chi-Square Test of Independence is commonly used to test the following: Statistical independence or association between two or more categorical variables. The Chi-Square Test of Independence can only compare categorical variables. It cannot make comparisons between continuous variables or between categorical and continuous variables.
SPSS for presentation and report writing As already said, the SPSS output viewer can be used as presentation and report writing tool, i.e. you might use it for simple presentations or table and charts heavy reports without using any other software.
APA doesn’t say much about how to report regression results in the text, but if you would like to report the regression in the text of your Results section, you should at least present the unstandardized or standardized slope (beta), whichever is more interpretable given the data, along with the t-test and the corresponding significance level.
Table 2: Correlation matrix Kaiser Meyer Olkin (KMO) and Bartlett’s Test (measures the strength of relationship among the variables) The KMO measures the sampling adequacy (which determines if the responses given with the sample are adequate or not) which should be close than 0.5 for a satisfactory factor analysis to proceed.