Here there will be some text explaining what the site is for and how it’s organized. Below this introduction will be a major header called Foundational Material with a series of expandable headers.
Here I will explain the difference between descriptive and inferential statistics and the basic purposes of each, including the fundamentals of hypothesis testing. I will also introduce students to the three major categories of data (categorical, ordinal, continuous)
Here I will describe the basics of experimental design, and the necessity of identifying the appropriate types of statistical analysis before, not after, carrying out an experiment
Here I will remind students of the three major categories of data (categorical, ordinal, continuous), maybe with a link back to Topic: What statistics are and what are they used for and have a flow diagram leading them through to a decision about what techniques to use, given the type of data they have. In this flow diagram I anticipate having a series of links to the sections described below, for example Statistics: Types of Analysis:Chi-squared tests.
Here I’ll provide more detail about the normal distribution, what types of statistical analysis assume that your data are normally distributed, transformations to help meet normality assumptions, and non-parametric alternatives to the basic analyses if normality assumptions cannot be met.
Here I’ll describe how data should be entered and organized prior to statistical analysis, including the importance of double-checking data entry, organizing variables in appropriate columns, and labelling the levels of independent categorical variables.
Here’ I’ll address some common misunderstandings of statistical description and hypothesis testing, such things as what a p-value is and what it isn’t, what confidence intervals mean, the difference between correlation and causation, etc.