HPE 505 Quantitative Research Methods in HPE

This course introduces a range of topics in statistics, including data management, hypothesis construction and testing, descriptive statistics, parametric and non-parametric approaches of statistical tests. Taking a conceptual approach, this course integrates theory, application, and hands-on SPSS operation. Upon completion of the course, learners will be able to choose the appropriate analytic method given the research question and the measurement scales of the data. Communicating the results of statistical analysis in a narrative and using graphs and tables are emphasized through the course.

Credits

2

Learning Objectives

1. Prepare a data file and data dictionary for statistical analysis;
2. Identify outliers and missing data;
3. Recognize different types of variables;
4. Construct frequency distributions;
5. Translate the research question in a null and alternative hypothesis;
6. Describe the relationship between Type I and II errors, significance level, p-value, and power;
7. Compute and interpret Pearson product moment correlation coefficient, Spearman’s rank-order correlation coefficient, and Kendall tau correlation coefficient;
8. Conduct independent samples and paired t-tests, one-way and factorial Analysis of Variance (ANOVA) and repeated-measures ANOVA;
9. Perform simple linear, multiple linear, logistic regression, and contingency table analyses;
10. Choose the appropriate analytic approach given the research question and the measurement scales of the data;
11. Communicate the results of statistical analysis in a narrative and using graphs, charts and tables.