Statistics How To

Binomial Proportions: Difference Between Two Groups

Intro to Statistics > Binomial Proportions Previous: Statistical Assumptions Analyzing the Difference Between Two Groups Using Binomial Proportions So far in Intro to Statistics, we’ve covered many essential foundations. Let’s put them into action while looking at another common type…

Central Hypothesis

Intro to Statistics > Part 6: The Central Hypothesis Previous: Statistics Case Studies What is the Central Hypothesis? The central hypothesis is another name for the Null Hypothesis. It’s central, not because you think or hope it’s true. Usually, it’s…

Calculating Confidence Intervals

Calculating Confidence Intervals With random sampling of binomial values (in-favor vs. not-in-favor; heads vs. tails): Sampling from populations with percent-in-favor close to 50% have wider sampling distributions than populations with percentages closer to 0% or 100%. Larger sample sizes have…

Frequentist Statistics: Definition, Simple Examples

Statistics Definitions > Frequentist Statistics: What are Frequentist Statistics? Frequentist statistics (sometimes called frequentist inference) is an approach to statistics. The polar opposite is Bayesian statistics. Frequentist statistics are the type of statistics you’re usually taught in your first statistics…

Statistics Case Studies: Decision Errors

Intro to Statistics > Statistics Case Studies Previous: Type I & Type II Errors. The following six short statistics case studies explore Type I Error and Type II Error under various circumstances. The odd numbered cases concentrate on Type I…

Type I & Type II Errors: Examples

Type I and Type II Errors: Examples We’ll start off using a sample size of 100 and .4 to .6 boundary lines to make a 95% confidence interval for testing coins. Any coin whose proportion of heads lies outside the…

Binomial Approximation

Intro To Statistics > Binomial Approximation Previous: The Limited Meaning of Statistical Significance Binomial Approximation with the Z-Distribution The z-distribution is important because it is the ultimate source of many of the formulas used in statistics. The sampling distributions for…

Bayesian Analysis: An Overview

Intro to Statistics > Bayesian Analysis Previous: Frequentist Statistics Bayesian analysis provides a special method for calculating probability estimates, for choosing between hypotheses, and for learning about population statistic values. To explore its basic workings, we’ll start with a scenario…

Statistical Significance: Definition, Examples

Statistics Definitions > What is Statistical Significance? Statistical Significance is a way to tell you if your test results are solid. Statistics isn’t an exact science. In fact, you can think of stats as very finely tuned guesswork. As stats…

False Discovery Rate: Simple Definition, Adjusting for FDR

Hypothesis Testing > False Discovery Rate Contents: What is the False Discovery Rate? FDR Formula FDR in hypothesis testing FDR in medical testing Adjusting the false discovery rate Case Example What is the False Discovery Rate? The false discovery rate…