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Educational statistics

Course Description: The course includes an introduction to the foundations, principles, and concepts of educational statistics, descriptive and inferential statistical methods related to frequency distributions and their graphical representations, measures of central tendency, measures of dispersion, standard scores, the normal distribution, the relationship between variables, the steps of testing the null hypothesis in one-way ANOVA, calculating one-way ANOVA using SPSS, and methods for studying differences between groups using parametric and non-parametric statistical methods.

Credit hours: 3

Objectives of the course :

The student should be familiar with basic statistical concepts such as sample, population, parametric statistics, descriptive statistics, inferential statistics, and parametric and nonparametric statistical methods, and how to use them. This includes data classification, graphical presentation, calculation of central tendency measures, understanding their relationships, calculation of dispersion measures, skewed distribution, how to verify the normality of grade distribution, application of some parametric statistical methods, some nonparametric statistical methods, the conditions for using each, how to interpret the results obtained, and how to calculate the effect size in each case.

Course outputs :

Knowledge and understanding:
Extracts the foundations, principles, and concepts of educational statistics.

– It covers descriptive and inferential statistical methods related to frequency distributions and their graphs.
- Identifies standard scores, the normal distribution, and the relationship between variables.
– Explains the steps of testing the null hypothesis in one-way ANOVA.
– Data analysis using SPSS is classified according to its types. .
- Recognizes methods for studying differences between groups using parametric and non-parametric statistical methods.
– Differentiate between the fundamentals of scientific research in educational statistics research.
Skills:
– Compares the advantages and disadvantages of dispersion measures.
– Draws the normal distribution curve and can interpret it. .
– Able to convert raw scores to standard scores. .
Selects the appropriate statistical method for data analysis. .
– Can use SPSS software for data analysis in their specialization.
Values, autonomy and responsibility:
— Applies scientific research ethics in educational statistics research.
He uses self-learning skills and technical means in statistical research.
– Used for communication and information retrieval in educational statistics.
– Communicates effectively within his research team for the Educational Statistics course.
His performance and the performance of his colleagues are based on what he studied in educational statistics.

Additional information:

Last Updated: 2026-05-11