Directional Hypotheses: One-Tailed vs. Two-Tailed Tests

Hypothesis testing
One-tailed tests
Two-tailed tests
Research methodology
Effect size

A comprehensive, evidence-based guide to formulating directional hypotheses (H₁: μ₁ > μ₂), the practical and theoretical distinctions between one-tailed and two-tailed tests, and why two-tailed tests are the standard in scientific research unless strong a priori directional predictions exist. Illustrated with R visualizations and examples from kinesiology and the humanities.

Mar 4, 2026
Ovande Furtado

Descriptive Statistics

mean
median
mode
variance
standard deviation
interquartile range
range
coefficient of variation

A rigorous, evidence-based introduction to descriptive statistics for beginner researchers in kinesiology and the humanities. Covers measures of central tendency and variability, the coefficient of variation, R-based visualizations, and best practices for reporting.

Mar 4, 2026
Ovande Furtado

Fundamentals of Inferential Statistics

inferential statistics
probability distributions
hypothesis testing
sampling error
confidence intervals
type I error
type II error
effect size
statistical power

A rigorous, evidence-based introduction to inferential statistics for beginner researchers in kinesiology and the humanities. Covers probability concepts, sampling distributions, confidence intervals, hypothesis testing, Type I/II errors, effect size, and statistical power—with R-generated visualizations and applied examples throughout.

Mar 4, 2026
Ovande Furtado
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