Explore fundamental concepts and techniques in biostatistics through a comprehensive 10-hour course. Delve into measurements, study designs, and frequency distributions. Master statistical measures like mean, median, and mode. Gain proficiency in probability theory, including binomial and normal distributions. Learn about statistical inference, hypothesis testing, and confidence intervals. Investigate correlation, regression, and multiple linear regression. Study t-distributions and ANOVA for comparing means. Examine nonparametric tests such as Kruskal-Wallis. Analyze categorical variables and proportions using appropriate statistical methods.
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
