Course Description

Psychologists are interested in understanding a variety of phenomena and they use a wide variety of methods and measures to study the objects of their interest. Regardless of the content or conditions for study, statistics serve as important tools for making sense of the data that are collected. We need statistics to describe the data clearly so that the findings can be communicated to others. We also need statistics to use a specific data set as a basis for more general conclusions. That is, we can use statistics to infer general conclusions from the data collected. In this course, we’ll primarily focus on inferential statistics as descriptive statistics have already been covered during your previous semester. Topics to be covered include measures of association, introduction to hypothesis testing, parametric tests, and nonparametric tests.

Objectives of the Course

This course aims to help you develop an understanding of major concepts that underlie the use of inferential statistics in psychological research and to help you learn how to choose and carry out statistical procedures that are appropriate for drawing pertinent inferences from your data. More specifically, this course entails the following objectives:

1. To familiarize students with basic concepts of hypothesis testing and its usage in psychology.
2. To help students understand the statistical theory behind parametric and non-parametric tests.
3. To make students cognizant of various measures of associations.
4. To enable students to undertake appropriate statistical analyses depending upon the nature of data and research objectives.
5. To make students understand and interpret statistical results in published research articles.

Learning Outcomes of the Course  

By the end of this course, students will be able to perform appropriate statistical analyses covering the course topics and also read some research journals. More precisely, at the end of this course, students should:

1. Understand the z, t, chi-square, and F probability distributions.
2. Appreciate the procedures of inferential statistical analysis concerning two population parameters, regression and correlation, analysis of variance, and analysis of categorical data.
3. Demonstrate proficiency in basic inferential statistical data analysis.
4. Comprehend and interpret statistical results in research articles accurately.

Course Plan

This course holds 3 credit hours. Accordingly, there would be two lectures per week. Each lecture would be of 90 minutes duration. The class will be held on every Thursday and Friday at 09:30 am for the regular semester and 2:00 pm for the self-support semester in the classroom of BS-VI. This course will be taught in a lecture/discussion format. Lectures are used to present and clarify issues from the set text and to discuss case studies. They will also include short interactive exercises. The mode of instructions would be English. Lectures may be facilitated through the use of transparencies on high definition projector and multimedia presentations for essential concepts. As appropriate, various activities and supplemental readings will be used to enhance the student’s understanding of the material. Classroom lectures/discussions/activities will focus on the topics listed in the course break down. Furthermore, lectures will not be limited to the material from the texts; rather they would be a source of additional information from the instructor.

Course Breakdown

Course Evaluation

The assessment of learning in this course would be undertaken through various assessment activities. There would be two formal examinations namely midterm and final term examinations. Besides these formal examinations, there would be two classroom quiz, two written individual assignments, and one group project that must be submitted in a written report and formally presented in the classroom. The relative distribution of marks across these assessment exercises is as follows:

Learning Resources

The instructor shall provide important web links for each chapter of the course for enhancing students’ learning. Relevant research articles for critical review shall also be provided by the instructor. The recommended texts for this course are as follows:

Gravetter, F. J. & Wallnau, L. B. (2013). Essentials of statistics for behavioral sciences. (9th ed.). New York: Thomson/Wadsworth.

The suggested readings for this course include but are not limited to:

Howell, D. C. (2008). Fundamental statistics for the behavioral sciences (6th ed.). Belmont, CA: Thomson.

Guilford, J. P. (1995). Fundamental statistics in psychology and education. (4th ed.). New York: McGraw-Hill.