Dive into the world of statistical inference through this comprehensive 90-minute tutorial on hypothesis testing and p-values. Explore key concepts such as understanding p-values, conducting t-tests for comparing means, and choosing appropriate statistical tests. Learn to perform hypothesis tests using Excel, grasp the differences between Type 1 and Type 2 errors, and understand statistical significance. Examine the relationship between correlation and causation, delve into Analysis of Variance (ANOVA), and practice calculating p-values. Gain insights into paired and independent samples for statistical analysis, equipping yourself with essential tools for data-driven decision-making and research interpretation.
Overview
Syllabus
Understanding Statistical Inference - statistics help.
P-value in statistics: Understanding the p-value and what it tells us - Statistics Help.
Hypothesis testing: step-by-step, p-value, t-test for difference of two means - Statistics Help.
Two means t-test in Excel - Statistics Help.
Statistical Tests: Choosing which statistical test to use.
The idea behind Inference - evidence!.
Choosing which statistical test to use: Practice examples.
Hypothesis test (t-test) for a mean in Excel - statistics help.
Type 1 and Type 2 errors - Statistics Help.
Understanding Statistical Significance - Statistics help.
Correlation does not imply #causation and other important statistical concepts.
Understanding Analysis of Variance (ANOVA) including Excel - Statistics Help.
P-value calculations: Understanding where the p-value comes from.
p-values - a quiz to develop understanding.
Paired samples and independent samples for statistical analysis - statistics help.
Taught by
Dr Nic's Maths and Stats
