## Conduct and Interpret a (Pearson) Bivariate Correlation

Conduct and Interpret a (Pearson) Bivariate Correlation What is a Bivariate (Pearson) Correlation? Bivariate Correlation is a widely used term in statistics. In fact, it entered the English language in 1561, 200 years before most of the modern statistic tests were discovered. It is derived from the Latin word correlation, which means relation. Correlation generally describes the effect […]

## Spearman Correlation in SPSS

Spearman Correlation in SPSS Suppose we want to answer the research question, “Are letter grades in reading and writing correlated?” We assume that all we have to test this hypothesis are the letter grades (A-F) achieved in reading and writing. Our reading and writing grades (Grade2 and Grade3) are ranked data and measured on an […]

## Conduct and Interpret a Spearman Rank Correlation

Conduct and Interpret a Spearman Rank Correlation What is a Spearman Correlation? A Spearman correlation coefficient is also referred to as Spearman rank correlation or Spearman’s rho. It is typically denoted either with the Greek letter rho (ρ), or rs. Like all correlation coefficients, Spearman’s rho measures the strength of association between two variables. As such, the Spearman […]

## Correlation (Pearson, Kendall, Spearman)

Correlation (Pearson, Kendall, Spearman) Correlation is a bivariate analysis that measures the strength of association between two variables and the direction of the relationship. In terms of the strength of relationship, the value of the correlation coefficient varies between +1 and -1. A value of ± 1 indicates a perfect degree of association between the two […]

## Factor Analysis vs Path Analysis – The Difference

Factor analysis and path analysis are both statistical techniques used in the field of multivariate analysis, particularly in the context of structural equation modeling (SEM). While they share some similarities, they serve different purposes and have distinct methodologies. Factor Analysis: Purpose: Factor analysis is primarily used to identify underlying factors or latent variables that explain […]

## How to do Mediation Analysis Using Multiple Regression Analysis

How to Testing Mediation Analysis with Regression Analysis Mediation analysis is a hypothesized causal chain in which one variable affects a second variable that, in turn,affects a third variable. The intervening variable, M, is the mediator. It “mediates” the relationship between a predictor, X, and an outcome. Graphically, mediation can be depicted in the following […]

## Linear vs. Logistic Probability Models: Which is Better, and When?

Interpretability Let’s start by comparing the two models explicitly. If the outcome Y is a dichotomy with values 1 and 0, define p = E(Y|X), which is just the probability that Y is 1, given some value of the regressors X. Then the linear and logistic probability models are: p = a0 + a1X1 + a2X2 + … + akXk (linear) ln[p/(1-p)] = b0 + b1X1 + b2X2 + … + bkXk (logistic) […]

## The Difference Between the Bernoulli and Binomial Distributions

You might already be familiar with the binomial distribution. It describes the scenario where the result of an observation is binary—it can be one of two outcomes. You might label the outcomes as “success” and “failure” (or not!). Or, if you want to get mathematical about it, you might label them “1” and “0.” You […]

## Logistic Regression Analysis: Understanding Odds and Probability

Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome. People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent. How Odds and Probability Differ They measure the same thing on different scales. Imagine how confusing it would be […]

## How to Conduct Probit and Logit Models (Binary Outcome Models)

Probit and Logit Models (Binary Outcome Models) Do you want to understand the factors that influence binary outcomes? Then you’ve come to the right place. In this article, we’ll delve into the world of Probit and Logit models, which are commonly used in statistical analysis to predict binary outcomes. Whether you’re a researcher, […]