SU LMS

Statistics in Education

Objectives

After studying the course, the students will be able to:

Comprehend the basic concepts of statistics;
Understand the statistical concepts more frequently applied in Education and other social sciences
Apply various statistical techniques in analyzing research data in Education and other social sciences
Apply appropriate statistics in qualitative and quantitative researches
Understand the advanced concepts of statistics e
specially multivariate analysis

Course Outline

Unit-1: Unit:2:	Introduction to statistics Inferential Statistics
				Concept of Inferential Statistics
				Parametric versus Non-parametric Tests
				Hypothesis Testing
				Level of Significance
				Types of Error
Unit-3:		Comparing Measures of Central Tendency between Groups
			Differences between Groups
			Comparing a Single Group
			Comparing Two Groups
			Comparing Two or More Groups
			Paired or Dependent Measures
			Two way ANOVA
			Factorial Analysis of Variance
Unit-4:		Correlation and Regression
			Correlation
			Properties of Correlation Co-efficient
			Factors Affecting Correlation
			Multiple Correlation Co-efficient
			Scatter Plots
			Cronbach's Alpha
			The Regression Line

Unit-5:	Probability and Distribution of Sample Means
		Concept of Probability
		Probability and the Normal Distribution
		The Distribution of Sample Means
		Probability and the Distribution of Sample Means
Unit-6:	Tests for Ordinal Data and Nominal Data
			Spearman’s Correlation
			Tests for Nominal Data
			Chi-Square Goodness-of-Fit
			Chi-Square Independence
			Cochran’s Q
			Phi or Cramer’s V (Correlations for Nominal Data)

Multivariate Analysis

Unit-7: Introduction

Introduction to Multivariate statist number, nature, and combination of variable In Multivariate statistics.
The Data Matrix
The Correlation Matrix
The variance –covariance Matrix
The sum of squares and crocs-Production Matrix
Residuals

Unit-8: Data preparation: screening data prior to Analysis

Accuracy of Data file
Honest Correlations
Missing data Analysis
Outlines
Normality
Exploratory Factor Analysis

Unit- 9: Multiple Regressions

General purpose and Description
Kinds of Research Question
Limitation to Regression Analysis
Fundamental Equations for Multiple Regressions

Unit- 10: Discriminate Analysis

General Purpose and Description
Kind of research Question
Limitation to Discriminate Analysis
Fundamental Equation for Discriminate Analysis
Types of Discriminate Function Analysis
Issues of Discriminate Analyses.

Unit-11: Logistic Regressions

General purpose Descriptions
Kinds of Research Question
Limitation to logistic Regression Analysis
Fundamental equations for logistic Regression
Types of logistic Regression
Issues of logistic Regression

Unit-12: Multivariate Analysis of Analysis of Variance & Covariance MANCOVA.

General Purpose and Description
Limitation to Multivariate Analysis of Variance (MANOVA) & MANCOVA
Fundamental Equations for multivariate Analysis of variance
Issues of MANOVA

Suggested Readings:

Cohen, L. Manion, L. and Morrison, K. (2007) Research methods in education (5th edition). London: Routledge.

Dunn, D. S., Smith, R. A, and Beins, B. C. (2007) Best practices in teaching statistics and research methods in the behavioral sciences. Lawrence Erlbaum Associates.

Gravetter, F. J. and Wallnau, L. B. (2004) Statistics for the behavioural sciences (6th edition). USA: Thomson and Wadsworth.

Greenacre, M. (2007) Correspondence analysis in practice (2nd edition). Chapman and Hall/CR.

Howell, D. C. (2007) Statistical methods for psychology (6th edition). USA: Thomson and Wadsworth.

Lomax, R. G. (2007). An introduction to statistical concepts (2nd edition). Lawrence Erlbaum Associates.

Statistics in Education

Statistics in Education

Other Courses by Dr. Muhammad Sarwar