Table of Contents
- 1 What kind of statistical test would I use if I have two variables with frequency data?
- 2 How do you check if two distributions are the same?
- 3 What would be an appropriate statistical test to evaluate whether the two samples have been drawn from the same population?
- 4 How do you determine statistical significance between two groups?
- 5 How do you use a t test in R?
- 6 How do you compare more than two groups in research?
What kind of statistical test would I use if I have two variables with frequency data?
A chi-square test is used when you want to see if there is a relationship between two categorical variables.
How do you check if two distributions are the same?
The Kolmogorov-Smirnov test tests whether two arbitrary distributions are the same. It can be used to compare two empirical data distributions, or to compare one empirical data distribution to any reference distribution. It’s based on comparing two cumulative distribution functions (CDFs).
What statistical test would be used to compare the mean ages in five independent populations?
(i) If you want to predict the value of a variable based on the value of five or more other independent variables, you could use Multiple Regression Analysis using SPSS Statistics!
What would be an appropriate statistical test to evaluate whether the two samples have been drawn from the same population?
The two-sample t-test (Snedecor and Cochran, 1989) is used to determine if two population means are equal. A common application is to test if a new process or treatment is superior to a current process or treatment. There are several variations on this test. The data may either be paired or not paired.
How do you determine statistical significance between two groups?
Subtract the group two mean from the group one mean. Divide each variance by the number of observations minus 1. For example, if one group had a variance of 2186753 and 425 observations, you would divide 2186753 by 424. Take the square root of each result.
What statistical tests are commonly used to analyze differences between groups?
The following statistical tests are commonly used to analyze differences between groups: A t-test is used to determine if the scores of two groups differ on a single variable. A t-test is designed to test for the differences in mean scores.
How do you use a t test in R?
Using t-tests in R. t-tests. One of the most common tests in statistics is the t-test, used to determine whether the means of two groups are equal to each other. The assumption for the test is that both groups are sampled from normal distributions with equal variances.
How do you compare more than two groups in research?
If you want to compare more than two groups, or if you want to do multiple pairwise comparisons, use an ANOVA test or a post-hoc test. The t-test is a parametric test of difference, meaning that it makes the same assumptions about your data as other parametric tests. The t-test assumes your data:
What is a t-test in statistics?
Originally for Statistics 133, by Phil Spector One of the most common tests in statistics is the t-test, used to determine whether the means of two groups are equal to each other. The assumption for the test is that both groups are sampled from normal distributions with equal variances.