Course Catalogue

Module Title: SOCS 112 Statistics for Social Research

Programme: Sociology B.A.

Credit Value: 12

 

General Objectives:

A basic understanding of statistics is crucial to the successful completion of the sociology major. In this module, students will learn to interpret and critically evaluate statistical data and analyses found in professional publications and in the mass media. This course will also train students to produce their own statistical descriptions and analyses of existing data using SPSS software. The module will introduce key statistical concepts such as: population, sample, variable, census, qualitative vs. quantitative data, distribution, relative risk, measures of central tendency, measures of dispersion, variance, correlation, probability theory, confidence intervals and hypothesis testing. Students will become familiar with various means of representing statistical data, such as: contingency tables, bar graphs, pie charts, dot plot, stem-leaf plot, histogram, scatter plot, and linear regression.

 

Learning Outcomes:

By the end of the course, students will be able to:

  • Understand the role of statistics in social research
  • Produce appropriate graphs and statistics to describe and analyze a data set
  • Read and interpret statistical output and graphs from both computer applications and the mass media (newspapers, magazines)
  • Understand the different types of relationships between variables
  • Select appropriate methods and statistical tools to solve a particular research question.
  • Produce and interpret the results of a regression/correlation analysis
  • Understand the role that probability plays in making statistical inference
  • Interpret the quality of statistical studies in the mass  media, particularly those concerning social issues
  • Write and present statistical concepts and the results of a data analysis

 

Learning and Teaching Approach Used:

This course will rely heavily on lecture, primarily due to the technical nature of the material being presented. However, the lectures will be as interactive as possible and use examples that have relevance for students in their daily lives. The aim, then, is to encourage as much involvement on the part of students as possible. In-class exercises will also invite more active learning on the part of students.

 

Assessment:

Continuous Assessment:                   40%

            Homework (pairs):    20%

Lab Reports (pairs):   10%    

            Mid term test:             10%

 

End of Session Assessment:               60%

            Final Exam:                60%

 

Subject Matter

  • Introduction to social statistics: object of inquiry in social research, role of statistics in social research, what are statistical techniques.
  • Level of measurement: Nominal level of measurement, ordinal level of measurement, interval level of measurement, randomness assumption.
  •  Graphic presentation: values of illustrations and graphs, frequency distribution, histogram, frequency polygon, bar graphs, pie charts
  • Measure of central tendency: Mode, median, mean.
  • Measure of variability: Muller’s and Schuessler’s index of qualitative variation, the range – interdecile range, interquartile range,  quartile deviation,  variance and standard deviation
  • The unit normal distribution and standard scores: standard scores, standard scores and the unit normal distribution, converting z-scores to raw scores, non normal distribution, and probability function of the unit normal distribution.
  • Hypothesis testing and statistical inference: Research hypothesis, null hypothesis, statistical hypothesis, confidence interval.
  • Interval level test for significance: single-sample test of significance, two-sample test of significance, two independent sample test, k-sample test: independent sample, two way analysis of variance.
  • Nominal test of Significance: Single-sample test: chi-square test, two-sample test: independent samples & related samples, k-independent sample test: chi square for k samples.
  • Ordinal level test of significance: two-sample test: independent samples, the sign test, k-sample test: independent sample.
  • Measure of association for two variables: measure of association for various level of measurement with two nominal variables, with two ordinal variables, with two interval variables. Measure of association for variables of different measurement levels.
  • K-variable measurement of association: Kandall’s coefficient, multiple correlations, partial correlation.

 

Reading List:

Textbook:  

Levin, J., & Fox, J. A. (2007). Elementary Statistics in Social Research. 10th Ed. India: Pearson Education.

 

Reference:

Weiss, N. (2007). Introductory Statistics. 7th Ed. Pearson Education

Champion, Dean. (1981) Basic Statistics for Social Research. 2nd Ed. NY. MacMillan,

Pal, N. (2005). Statistics: Concept and Applications. 2nd Ed. India: Prentice Hall.

Date: March 2009