outline

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WOLAITA SODO UNIVERSITY
COLLEGE OF NATURAL AND COMPUTATIONAL SCIENCES
DEPARTMENT OF STATISTICS
Course Outline: Statistics for Sociologists (SOCI-2101)
Course Title/Code: Statistics for Sociologists (SOCI-2101)
Credit: 7 EtCTS
Academic Year: 2008/2016
Semester: II
Program: Undergraduate
Instructor’s Name: Eyasu A.(MSc)
E-mail: eyasu.mastmo@gmail.com
Student’s work load
Lecture Tutorial Assessment Assignments Home study Total
42 30 20 42 55 189
A WORD ABOUT CONDUCT
• Basic principles
1. Every student has the right to learn as well as responsibility not to deprive others of their
right to learn.
2. Every student is accountable for his or her own actions.
In order for you to get the most out of this class, please consider the following:
i. Attend all scheduled classes and arrive on time. Late arrivals and early departures are
very disruptive and violate the first basic principle.
ii. Please do not schedule other activities during this class time. I will try to make class as
interesting and informative as possible, but I can’t learn the material for you.
iii. Please let me know immediately if you have a problem that is preventing you from
performing satisfactorily in this class.

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Course Description
This module starts with introducing basic concepts, applications, uses and limitations of
Statistics. It also introduces methods of data collection and presentation; measures of central
tendency, measures of variation (dispersion); elementary probability; probability distributions;
sampling and sampling distribution of the sample mean and proportion; one and two sample
inferences; Analysis of Variance (ANOVA); and simple linear regression and correlation.
Course Objectives
The main objective of this module is to introduce students to the basics of statistics and its use in
sociological research. It aims at imparting to students the application of statistical techniques and
the interpretation of statistical results.
Competency/ Learning Outcomes
At the end of the course students are expected to:
Have a broad knowledge of the basic understanding of statistical techniques
demonstrated through principles of data collection, descriptive statistics, probability,
probability and sampling distributions, statistical inference and linear regression.
Understand the methods of data collection, organization, presentation, analysis and
interpretation;
Know what is meant by sample space, event, relative frequency, probability, conditional
probability, independence, random variable, probability distribution, probability density
function, expected value and variance;
Be familiar with some standard discrete and continuous probability distributions;
Be able to use standard statistical tables for the Normal t and chi-square distributions;
Be able to differentiate between common types of data, and display them appropriately;
Learn some desirable properties of point estimators;
Recognize the additional benefits of calculating interval estimates for unknown
parameters;
Understand the framework of hypothesis testing for carrying out statistical inference;

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Be able to produce and interpret interval estimates and tests of hypotheses correctly in
some simple cases;
Have basic skills in exploratory data analysis.
Contents
1. Section one: Introducing statistics: Definition and classification of statistics; stages in
statistical investigation; applications, uses and limitations of statistics; and scales of
measurement.
2. Section two: Methods of data collection and presentation: Introduction methods of
data collection focusing on sources and types of data, frequency distributions and
diagrammatic and/or Graphical presentation of data.
3. Section three: Measures of Central Tendency: Objectives of measuring central
tendency, the summation notation, properties of measures of central tendency, types of
measures of central tendency and quantiles.
4. Section four: Measures of variation (Dispersion): Objectives of measuring variation;
absolute and relative measures; types of measures of variation; and the standard scores,
moments, skewness and kurtosis.
5. Section five: Elementary probability: Definition of some probability terms, counting
rules, probability of an event, probability rules, and conditional probability and
independence.
6. Section six: Probability distributions: Definition of random variables and probability
distributions, introducing expectation, common discrete probability distributions and
common continuous probability distributions.
7. Section seven: sampling and sampling distribution of the sample mean and
proportion: Discussing inter alia basic concepts, reasons for sampling, types of
sampling techniques, basic concepts and definitions of probability and non-probability
sampling, sampling distribution of the sample mean and proportion and central limit
theorem.

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8. Section eight: One sample inference: Point and interval estimation of the mean and
proportion, hypothesis testing about the mean and proportion, sample size determination
and Chi-Square test of association.
9. Section nine: Two sample inference: Inferences about differences between two means,
inferences about differences between two proportions, tests of hypotheses on the ratio of
the variances of two normally distributed populations, and sample size in comparative
studies.
10. Section ten: Analysis of Variance (ANOVA): One-way ANOVA and multiple
comparisons (Fisher’s Least Significant Difference and Scheffe’s Method)
11. Section eleven: Simple Linear Regression and Correlation: Covariance and
correlation coefficient, rank correlation coefficient, simple linear regression, and
multiple linear regression analysis
Reading Materials
Text Books:
Bluman, A.G. (1995). Elementary Statistics: A Step by Step Approach (2nd edition).Wm. C.
Brown Communications, Inc.
Snedecor, G.W and Cochran, W.G. (1980). Statistical Methods, 7th edition
References:
Eshetu Wencheko (2000). Introduction to Statistics. Addis Ababa University Press.
Freund, J.E and Simon, G.A. (2005). Modern Elementary Statistics (9th Edition)
Spiegel, M.R. and Stephens, L.J. (2007). Schaum's Outline of Statistics, Schaum's Outline Series
(4th edition). McGraw-Hill.
Mode of Assessment:
Students will be graded on the basis of their performances in:
Class attendance/activity…………………………. 10%
Quiz’s/Tests/Assignments…………………………. 40%
Final Exam………………………………………… 50%