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
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