EPSY 326 : Inferential Statistics

Department

Department of Educational and Psychological Sciences

Academic Program

Bachelor in Education and Psychology

Type

Compulsory

Credits

02

Prerequisite

EPSY 314

Overview

Enable the student to use more accurate methods in inferential statistics to describe the measured and observed psychological characteristic and to identify in a preliminary manner ways to detect differences and their statistical significance, correlations and statistical significance. As well as recognizing the shape of the results as they appear when using the SPSS package.

Intended learning outcomes

The student must be able to:

1. The student should recall the concept of inferential statistics, population, sample, inspection, statistical hypotheses.

2. The student should explain the conditions and uses of the test (T) to indicate the differences in averages.

3. The intended student should mention the significance of the differences between two unrelated averages of two different groups in number

4. The student should explain the chi-square test - its concept - its uses.

5. The student should mention the methods of inferential statistics for non-parametric hypothesis tests

6. The student should compare the population, sample and inspection,

7. The student should retrieve the conditions for the uses of the test (T) to indicate the differences in averages.

8. The student should analyze the significance of the differences between two unrelated averages for two groups of equal numbers.

9. The student should demonstrate the concept, use and methods of calculating the chi-square

10. The student should analyze the methods of inferential statistics for non-parametric hypothesis tests

11. The student should design a printed worksheet in which he explains the concept of inferential statistics, population, sample and inspection with illustrative examples.

12. The student should present a visual presentation explaining the meaning of the significance of the differences between two unrelated averages for two groups of equal numbers with illustrative examples.

13. The student should apply the significance of the differences between two unrelated averages for two different groups in number.

14. The student should explain through a worksheet the content of the Colomogrove Smarnov test for one sample

15. The student should design a slide show in which he explains the methods of inferential statistics for non-parametric hypothesis tests with examples.

16. The student should be able to communicate and communicate in writing and orally

17. The student should be able to use modern technology .

18. Works in a team spirit and accepts constructive criticism

Ability to self-learning and continuous

Teaching and learning methods

· Lecture

· Brainstorming

· Collaborative Learning

· Present examples and problems during the lecture.

· The use of semi-internet in enhancing the content of the article.

Methods of assessments

Written test (e.g. multiple-choice {closedbook}, closed question type written test {open book} or mix)oral testContinuous constructive assessment (periodic)Scientific activities (e.g. writing a report or presenting an exhibition)DiscussionsPractical test

Course contents.

The week	Scientific topic
1	Definition of inferential statistics, normal distribution
2	Population, sample and inspection, statistical hypotheses
3	Test (T) to indicate mean differences
4	Terms of Use Test (T) The significance of the differences for the mean of a sample in the population, the significance of the differences between two unrelated averages of two different groups in number.
5	First midterm exam (two hours)
6	The significance of differences between two unrelated averages of two groups of equal numbers.
7	Analysis of variance: (one-way-two-way)
8	Chi-square test - concept - uses
9	Methods of calculating the chi-square: a. Calculating Ka2 from the frequency table (1×2), B. Calculating Ka2 from the frequency table (1×n).
10	Second midterm exam (two hours)
11	c. Calculation of Ka2 from the frequency table (2×2) double classification.
12	d. Calculation of Ka2 from the frequency table (2×n) double classification.
13	Inferential statistics methods for nonparametric hypothesis tests · Single-sample colomogrove Smernov test · Mann Whitney Test
14	· Kruskal-Wallis Test · Wilcoxon Test
15-16	Final Exam

References

Reference title	Publisher	Published	Author	Country of publication
Descriptive statistics in educational sciences	Dar Al Masirah	2007	Adnan Hussein Aljardi	Oman
Descriptive and inferential statistics in psychology - education and sociology	Shugairi Library for Publishing and Distribution	2009	Zakaria El-Sherbiny	Cairo

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