Course Code & Number:
Level of Course:
Pre-requisites & Co-requisites:
Final Exam - 40%
Quiz - 10%
Lab Work - 30%
Writing assignments (Oral, Poster) - 20%
Introduction to Statistics for Social Sciences. How statistical analysis is used in Social Sciences? Testing hypotheses. Levels of measurement and forms of data. Defining variables. Gathering the data. Operational definitions. Validity. Reliability. Measuring central tendency. Measuring dispersion. Constructing and interpreting contingency tables. Statistical inference and tests of significance. What is statistical inference? Probability distributions and one-sample z and t tests . Two-sample t tests. One-way analysis of variance. Measuring association in contingency tables. The chi-square test . Additional aspects of correlation and regression analysis. Partial correlations and causal models. Multiple correlation and the coefficient of multiple determination . Multiple regression. The standardized partial regression slope. Using a regression printout . Stepwise multiple regression. Computer applications. Emphasizes social science examples and cases.
Upon succesful completion of this course, a student will be able to
1. Explain the fundamental statistical concepts covered throughout the course.
2. Use graphical and numerical methods to summarize data.
3. Calculate the probabilities of events under natural assumptions on the population.
4. Analyze data sets to make inference about characteristics of a population.
5. Apply statistical techniques in problems of interest and obtain useful conclusions.
6. Use SPSS program to analyze data sets