Statistics

Clear examples in R. Count data; Hermite regression; Poisson regression; Negative binomial regression; Zero-inflated regression; Vuong test

Learn, step-by-step with screenshots, how to run a Poisson regression analysis in SPSS Statistics including learning about the assumptions and how to interpret the output.

An introduction to the one-way ANOVA including when you should use this test, the test hypothesis and study designs you might need to use this test for.

Learn, step-by-step with screenshots, how to run a multiple regression analysis in SPSS Statistics including learning about the assumptions and how to interpret the output.

How to perform a simple linear regression analysis using SPSS Statistics. It explains when you should use this test, how to test assumptions, and a step-by-step guide with screenshots using a relevant example.

A list of our statistical guides which have step-by-step instructions with screenshots, notes and explanations to guide you through the SPSS Statistics procedure required to analyse your data in SPSS.

How to read and run correlation plots in Python Pandas

Course book for Data Analysis and Statistics with R (APS 240) in the Department of Animal and Plant Sciences, University of Sheffield

Many of the following statistical tests are rarely discussed in textbooks or in college classes, much less in data camps. Yet they help answer a lot of differe…

ANOVA allows us to move beyond comparing just two populations. With ANOVA we can compare multiple populations and even subgroups of those populations. In thi...

One and two-way ANOVA in Python. This article explains ANOVA model, formula, calculation, multiple pairwise comparisons, and results interpretation

Step-by-step instructions, with screenshots, on how to use the Kaplan-Meier method in SPSS. This includes the SPSS Statistics output and how to interpret the output.

Using the one-way ANOVA as a means to control the increase in Type 1 errors with multiple t-tests and understanding the assumptions underlying the test.

To interpret data, consultants need to understand distributions. This article discusses how to understand different types of statistical distributions, understand the uses of different distributions, and make assumptions given a known distribution.

Analysis of variance? Discourse analysis? Grounded theory? With so many data analysis methods, it can be tough to keep up. Here's an overview of the basics.

Turn raw data into useful, actionable insights—discover the top data analysis techniques here, from regression analysis and the Monte Carlo simulation throug...