Hypothesis Testing
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Post-Hoc Tests: Understanding the Tools to Control Type I Error
When performing statistical analyses, particularly in the context of ANOVA (Analysis of Variance), researchers are often faced with the question: “Which groups are significantly different from each other?” While ANOVA tells us if there is a significant difference somewhere among the group means, it does not specify where these differences lie. This is where post-hoc… Continue reading
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When Averages Collide: The One-Way ANOVA
When working with data, researchers and analysts often need to compare the averages (or means) of different groups to determine if they differ significantly. This is where a One-Way Analysis of Variance (ANOVA) comes into play. Continue reading
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Testing Averages Made Simple: The One-Sample t-Test Explained
If you’ve ever wanted to determine whether the average of a single group differs significantly from a known or hypothesised value, then the one-sample t-test is your statistical tool of choice. In this blog post, we’ll demystify the one-sample t-test, explain when and how to use it, and walk through a real-world example to solidify… Continue reading
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Independent T-Test: The Statistics Behind Comparing Groups
When you have two groups and a burning question—Are these groups significantly different?—the independent t-test provides the answer. Whether you’re testing the effectiveness of two treatments, comparing sales from two marketing strategies, or analysing test scores from two teaching methods, the independent t-test is the statistical tool to use. Continue reading
Simplifying Statistics 
