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This web site offers free resources for students and researchers working with statistics in the social sciences. All the calculators and tools featured here have been designed with ease of use and clarity of presentation in mind.
Here you'll find a set of statistics calculators that are intuitive and easy to use. Included are a variety of tests of significance, plus correlation, effect size and confidence interval calculators.
Further Information. A t-test is used when you're looking at a numerical variable - for example, height - and then comparing the averages of two separate populations or groups (e.g., males and females).. Requirements. Two independent samples; Data should be normally distributed; The two samples should have the same variance; Null Hypothesis
Pearson Correlation Coefficient Calculator. The Pearson correlation coefficient is used to measure the strength of a linear association between two variables, where the value r = 1 means a perfect positive correlation and the value r = -1 means a perfect negataive correlation. So, for example, you could use this test to find out whether people's height and weight are correlated (they will be ...
A simple wizard to help social science students select an appropriate statistics test.
Which Statistics Test? Contact; Chi-Square Test Calculator. This is a easy chi-square calculator for a contingency table that has up to five rows and five columns (for alternative chi-square calculators, see the column to your right). The calculation takes three steps, allowing you to see how the chi-square statistic is calculated.
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Social Science Statistics offers free resources for students and researchers working with statistics in the social sciences. It grew out of statistical tests that were devised to analyse the data generated at the Philosophy Experiments web site.
A set of free and easy statistics tutorials, including introductory SPSS, suitable for social science students.
Which Statistics Test? Contact; Quick P-Value Calculators. This is a set of very simple calculators that generate p-values from various test scores (i.e., t test, chi-square, etc). P-value from Z score. P-value from t score. P-value from chi-square score.