This course covers the fundamentals of biostatistics, including measurements, study designs, probability distributions, hypothesis testing, confidence intervals, correlation, regression, ANOVA, and nonparametric tests. Students will learn how to analyze data, make inferences, and draw conclusions in the field of biostatistics. The course uses lectures to teach these concepts and is intended for individuals interested in statistics and its applications in the field of biology and healthcare.
Overview
Syllabus
Measurements - Biostatistics (Unit 1 Lecture).
Study Designs - Biostatistics Lecture 2 Part 2.
Frequency Distribution and StemPlot (Stem and leaf plot) - Biostatistics Lecture Unit 3.
Mean Median Mode -- Biostatistics I.
Introduction to Probability - Biostatistics Lecture 5.
Binomial Probability Distribution - Biostatistics.
Continuous Random Variable, Continuous Distribution and Normal Probability Distribution.
Introduction to Statistical Inference, Sampling Behavior of a Mean, Count and Proportion.
Hypothesis Testing, Null and Alternative Hypotheses, Test Statistic, P-Value, Significance Level.
Confidence Intervals and Estimation, Confidence Interval for μ when σ is known - Biostatistics.
Correlation and Regression, Hypothesis Testing using Correlation and Regression - Biostatistics.
Biostatistics - Multiple Linear Regression.
t Distribution Test: Inference About a Mean - Biostatistics.
t test to compare two Independent Means, Inference About the Mean Difference - Biostatistics.
One-Way ANOVA: Comparing Several Means - Analysis of Variance - Biostatistics.
Introduction to Nonparametric Tests - Kruskal-Wallis test - Biostatistics.
Inference About a Proportion: Analysis categorical variables - Nonparametric Tests: Biostatistics.
Taught by
Charles Edeki -- Math Computer Science Programming
