This course covers the concepts of statistical inference, focusing on topics such as samples from a normal distribution, central limit theorem, standard error of the mean, confidence intervals, and hypothesis testing. The course teaches students how to understand sampling distributions, confidence intervals, and hypothesis tests, including null and alternative hypotheses, test statistics, critical values, rejection regions, p-values, errors, and power. The teaching method includes tutorials and lectures presented in video format. This course is intended for beginners in statistics and those interested in learning about statistical inference using R programming.
Overview
Syllabus
Samples from a Normal Distribution | Statistics Tutorial #4 | MarinStatsLectures.
Central Limit Theorem & Sampling Distribution Concepts | Statistics Tutorial | MarinStatsLectures.
Standard Error of the Mean: Concept and Formula | Statistics Tutorial #6 | MarinStatsLectures.
Confidence Interval Concept Explained | Statistics Tutorial #7 | MarinStatsLectures.
Hypothesis Testing Explained | Statistics Tutorial | MarinStatsLectures.
What is a Sampling Distribution? | Puppet Master of Statistics.
What is a Confidence Interval? | Puppet Master of Statistics.
What is a Hypothesis Test and a P-Value? | Puppet Master of Statistics.
Hypothesis Testing: The Big Picture (One Sample t-test) I Statistics 101 #1 | MarinStatsLectures.
Hypothesis Testing: Null & Alternative Hypothesis I Statistics 101 #2 | MarinStatsLectures.
Hypothesis Testing: Test Statistic (one sample t test) I Statistics 101 #3 | MarinStatsLectures.
Hypothesis Testing: Critical values & Rejection Regions I Statistics 101 #4 | MarinStatsLectures.
Hypothesis Testing: P Value (one sample t test) I Statistics 101 #5 | MarinStatsLectures.
Hypothesis Testing: Conclusion (one sample t test) I Statistics 101 #6 | MarinStatsLectures.
Hypothesis Testing: Errors and Power (one sample t test) I Statistics 101 #7 | MarinStatsLectures.
Taught by
MarinStatsLectures-R Programming & Statistics
