Likert scale survey data analysis and interpretation on Excel and SPSS

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Questionnaire items
Operationalization
Codes and labels
Descriptive statistics
Mean, standard deviation, min, max, and range
Frequencies and percentages
Cronbach alpha reliability
Exploratory factor analysis
Outlier removal
Sociodemographic variables in one table
Custom table function
Z score data transformation
Correlation
Regression
ANOVA
Chart and diagrams
Maslach burnout scale of exhaustion, cynicism and reduced efficacy
Self determination theory
Motivation and its types
Internal motivation
External motivation
Amotivation
The role of motivation on academic burnout
Millennials
Generation Z
Generation Alpha
Data interpretation and report in APA
✨Social media:
Mohamed Benhima, PhD
Email: datanalysis93@gmail.com
WhatsApp: +212619398603 / wa.link/l6jvny
#questionnaire

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Опубликовано:

30 мар 2024

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Комментарии : 6

@yohannaagbanaji8012 Месяц назад

It feels great to find your videos.

@kalyansundarsamanta 2 месяца назад

Nice presentation. Sir, what is Zscore? How can I conduct convergent and discriminant validity?

@chefberrypassionateresearcher 3 месяца назад

If I do ANOVA after calculating the MEAN (which will form my continuous dependent variable) of all 6 items ( MOT 1, MOT 2, MOT 3, MOT 4, MOT 5, MOT 6), then how can i find out difference between my three groups (independent categorical variable), on the basis of any specific motivation item out of these: ( MOT 1, MOT 2, MOT 3, MOT 4, MOT 5, MOT 6) ? Sir, please suggest the right way to do it. I know ANOVA can give me significant difference between the three groups with post hoc analysis, but how can I ascertain the difference on a specific item level, if I am transforming the 6items to a mean value? Is it better to do MANOVA or apply any other technique for this purpose??

@MohamedBenhimaPhD 3 месяца назад

You need to test Cronbach alpha reliability. Based on that, you can group the items and run ANOVA or Kruskal Walis H Test depending on the normality and homogeneity of the variance as well.