Quantitative Data Analysis Seminar for Researchers in Social Sciences


Description

This 20-hour seminar is designed to introduce researchers in social sciences to the quantitative data analysis procedures. Using SPSS and authentic research data (both small scale and large-scale), the participants will learn how to perform descriptive and inferential statistical analyses. Both parametric and nonparametric inferential Statistical analyses will be covered in this seminar.

Objectives

In completing this seminar, the participant must be able to:
1. Define terminology associated with quantitative research;
2. Identify the problems that are associated with analyzing statistical data;
3. Use computer programs (e.g., Excel, SPSS) to perform data preparation for analysis;
4. Use SPSS to perform appropriate statistical analyses for existing data;
5. Interpret and report the results in a scholarly way;
6. To implement a data analysis project for existing data.

CalendarModule #1 (2 Hours)
Theoretical Foundations of Quantitative Research
∙ An overview of quantitative research          
∙ Measurement issues in quantitative research
∙ Basic concepts in statistics                            
∙ Ethical issues in quantitative research

Module #2 (3 Hours)
Descriptive Statistics
∙ Organizing and graphing data                     
∙ Measures of variability
∙ Measures of central tendency                      
∙ The normal curve and standard scores

Module #3 (4 Hours)
Association and Prediction
∙ Pearson correlation                                         
∙ Simple linear regression
∙ Spearman correlation                                     
∙ Multiple linear regression

Module #4 (4 Hours)
Parametric Inferential Statistics                    
∙ Analysis of variance (ANOVA)
∙ Basic hypothesis testing                                 
∙ Analysis of covariance (ANCOVA)
∙ t tests                                                                  
∙ Multivariate analysis of variance (MANOVA)

Module #5 (4 Hours)
Nonparametric Inferential Statistics
∙ Chi square goodness of fit                             
∙ Chi square test of independence
∙ Mann-Whitney U test                                    
∙ Wilcoxon test
∙ Kruskal-Wallis H test                                    
∙ Friedman test

Group Research Consulting (3 Hours)
Project/Thesis/Dissertation Research Design: Choosing the research topic; Stating the research questions; Planning data collection and analysis procedures Instrument Development: Quantitative research instruments (e.g., questionnaires, tests); Qualitative research instruments (e.g., interview protocols) Data Analyses: Data entry and preparation; Qualitative data analysis; Quantitative data analyses (e.g., univariate and multivariate statistics; SEM, HLM, IRT, G-theory analyses) Grant Proposals: Writing the grant proposal; Budget justification Publications: Publishing a journal article; Publishing a book