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Data Analysis and Statistical Inference in Social Work I Lab


Course Description

Companion lab course for Data Analysis and Statistical Inference in Social Work I. The two broad goals of this course are to enable students to understand statistical theory and its relevance to social work and to enable students to perform and interpret basic bivariate and multivariate statistical analysis.


Athena Title

Social Work Stats I Lab


Corequisite

SOWK 8176


Semester Course Offered

Offered fall


Grading System

S/U (Satisfactory/Unsatisfactory)


Course Objectives

By the end of this course, students should be able to: a) Describe the nature of variables and manipulate them appropriately where necessary. b) Choose and apply appropriate descriptive and bivariate statistical techniques to address research questions and hypotheses. c) Use IBM SPSS for univariate, bivariate, and multivariate data analyses. d) Interpret findings. e) Communicate results clearly and effectively, using the latest APA format. f) Understand statistical assumptions and how to detect and address violations. g) Recognize strengths and weaknesses in various analyses and formulate constructive critiques. h) Appreciate current controversies related to topics addressed in this course. i) Gain beginner understanding and application of multivariate analyses. j) Evaluate empirical work relative to use of theory, sample design, instrumentation, method of data collection, and significance of findings for social work practice or policy.


Topical Outline

1. Introduction to Data, Introduction to SAS 2. Data Basics: Measures of Central Tendency, Frequency Distribution 3. Univariate Analysis: Normality, Z Tests, Binomial 4. Bivariate Analysis: T-Tests 5. Bivariate Analysis: Chi-Square 6. Bivariate Analysis: Correlations 7. Multivariate Analysis: ANOVA 8. Multivariate Analysis: Linear Regression 9. Multivariate Analysis: CMH 10. Principal Components