EHRD 690 - Theory of EHRD Research: Statistics I
EHRD 690 - Theory of EHRD Research: Statistics I
EHRD 690 introduced foundational statistical concepts used in HRD research and organizational decision-making. The course emphasized correlation analysis, regression, hypothesis testing, confidence intervals, independent and paired samples t-tests, and applied data analysis using SPSS. Through conceptual exercises and applied scenarios, I developed the ability to interpret statistical output and translate findings into organizational insight.
Foundational Statistical Practice
Correlation & Regression Practice
This practice assignment demonstrates foundational understanding of correlation coefficients (r, rs, rpb, φ), regression interpretation, coefficients of determination, slope and intercept interpretation, and statistical terminology. It reflects conceptual understanding of linear relationships and predictive modeling fundamentals.
Hypothesis Testing & Confidence Intervals
This assignment required application of one-tailed and two-tailed hypothesis testing, independent and paired sample t-tests, z-tests, and construction of confidence intervals. These exercises reinforced statistical decision rules, critical values, and interpretation of inferential results.
Applied Data Analysis – Scenario Projects
Organizational Salary Analysis (SPSS)
In this applied scenario, I analyzed Major League Baseball salary data using SPSS to evaluate payroll disparities, team salary averages, positional salary differences, and compensation distribution. The analysis included descriptive statistics, standard deviations, comparative means, and interpretation of financial variance.
This project demonstrates my ability to:
Conduct descriptive statistical analysis
Interpret large datasets (N = 877)
Translate quantitative findings into strategic recommendations
Apply regression and comparative analysis techniques
Independent Samples t-Test (Educational Performance Analysis)
This applied research scenario examined differences in academic performance between students with AP credit and those without. Using an independent samples t-test, I evaluated statistical significance, tested variance assumptions, and interpreted confidence intervals to determine meaningful differences between groups.
The project required:
Hypothesis formulation
Assumption testing (Levene’s test)
SPSS output interpretation
Practical application of inferential statistics
Professional Reflection
EHRD 690 significantly strengthened my quantitative literacy and confidence in interpreting statistical data. Prior to this course, I understood performance metrics conceptually but lacked technical fluency in hypothesis testing and SPSS analysis.
This course enhanced my ability to:
Distinguish between correlation and causation
Select appropriate statistical tests based on data type
Interpret p-values and confidence intervals accurately
Translate statistical findings into practical organizational implications
In my HR role, these competencies directly support data-driven decision-making in areas such as turnover analysis, performance evaluation, compensation review, and engagement assessment.