Which stats test to use

For a more theoretical background on statistical testing, please read the below articles:. The displayed tests are the most commonly used tests in statistics. Please scroll down to see the grid. Validity conditions we propose are rules of thumb. There are no precise rules in literature. Read our guide Which statistical model should you choose to learn how to choose the right model for your analysis i. All Rights Reserved. Toggle SideBar. Have a Question? Ask or enter a search term here.

My profile. Which statistical test should you use? What is a statistical test? A guide to choosing an appropriate test according to the situation XLSTAT provides a high number of statistical tests. For a more theoretical background on statistical testing, please read the below articles: What is a statistical test?

What is a difference between paired and independent samples tests? What is the difference between a parametric and a nonparametric test? What is the difference between a two-tailed and a one-tailed test? How to interpret the output of a statistical test: the significance level alpha and the p-value The grid The displayed tests are the most commonly used tests in statistics. Biserial correlation test Normality of the quantitative variable Test the association between a series of proportions and an ordinal variable Contingency table or proportions and sample sizes Proportions do not change according to the ordinal variable Did birth rates change from year to year during the last decade?

Cochran-Armitage trend test Test the association between two tables of quantitative variables Two tables of quantitative variables Tables are independent Does the evaluation of a series of products on a series of attributes change from a panel to another?

RV coefficient test Test the association between two proximity matrices Two proximity matrices Proximity matrices are independent Is geographic distance between populations of bees correlated with genetic distance? Mantel's test Time series tests Test the presence of a trend across time One series of data sorted by date time series There is no trend across time for the measured variable Did stock value change across the last 10 years?

Mann-Kendall trend test Tests on distributions Compare an observed distribution to a theoretical one Measurements of a quantitative variable on one sample; parameters of the theoretical distribution The observed and the theoretical distributions are the same Do the salaries of a company follow a normal distribution with mean and standard deviation ? To look for an association between variables. Previous Next Start over. Need some help? Find content related to this author. A textbook example is a one sample t-test : it tests if a population mean -a parameter- is equal to some value x.

This test involves only 1 variable even if there's many more in your data file. Note that the subpopulations are represented by subsamples -groups of observations indicated by some categorical variable. Association measures are numbers that indicate to what extent 2 variables are associated. The best known association measure is the Pearson correlation : a number that tells us to what extent 2 quantitative variables are linearly related.

The illustration below visualizes correlations as scatterplots. The simplest example is simple linear regression as illustrated below. Prediction analyses sometimes quietly assume causality : whatever predicts some variable is often thought to affect this variable. Depending on the contents of an analysis, causality may or may not be plausible. Campbell MJ, Machin D.

Chichester: Wiley, Stats Flow Chart. How to use nQuery. Guide to Sample Size. Written by nQuery Team. March 2, Types of Statistical Tests Updated: March In terms of selecting a statistical test, the most important question is "what is the main study hypothesis? The decision of which statistical test to use depends on: The research design The distribution of the data The type of variable When choosing the correct test, ask yourself the following questions: What kind of data have you collected?

What is your goal? Sample Size and Power Analysis 2. Hypothesis Testing 3. Statistical Power 4. Effect Size 5. Confidence Intervals 6. Bayesian Statistics 7. Adaptive Clinical Trials 8. Previous Story. Next Story. October 28, September 30, How to predict key events in survival analysis trials. August 26, Subscribe by Email. No Comments Yet Let us know what you think. Overview What's New.