A series of free Statistics Lectures with lessons, examples & solutions in videos.
This is page twenty-one of the series of free video lessons, “Statistics Lectures”. These lectures discuss various types of samples t-test, covering independent samples t-test, confidence intervals for independent samples t-test, effect size for independent samples t-test and dependent samples t-test.
19: Effect Size, Power, Statistical vs. Practical Significance
20: One Sample z-Test & One Sample t-Test
22: More Samples t-Test
23: Introduction To ANOVA & One-Way ANOVA
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A statistics teacher wants to compare his two classes to see if they performs any differently on the tests he gave that semester. Class A has 25 students with an average score of 70, standard deviation 15. Class B has 20 students with an average score of 74, standard deviation 25. Using alpha 0.05, did these two classes perform differently on the tests?
We use the Independent Samples t-Test to test if two sample means are different from one another.
After the t-Test, confidence intervals can then be constructed to estimate how large that mean difference is.
The effect size allows us to measure the magnitude of mean differences.
Researches want to test a new anti-hunger weight loss pill. They have 10 people rate their hunger before and after taking the pill. Does the pill do anything? Use alpha = 0.05.
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