Statistics Lectures - 22: More Samples t-Test

A series of free Statistics Lectures with lessons, examples & solutions in videos.

This is page twenty-two of the series of free video lessons, “Statistics Lectures”. These lectures continues the discussion on samples t-test from the previous lectures, covering confidence intervals for dependent samples t-test, effect size for dependent samples t-test, z-test for proportions.

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Related Pages
20: One Sample z-Test & One Sample t-Test
21: Various Types Of Samples t-Test
24: Repeated Measures ANOVA & Factorial ANOVA
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Statistics - Lecture 66: Confidence Intervals For Dependent Samples t-Test

We use the Dependent Samples t-Test to test if two sample menas are different from one another.
After the t-Test, confidence intervals can then be constructed to estimate how large that mean difference is.

Statistics - Lecture 67: Effect Size For Dependent Samples t-Test

The effect size allows us to measure the magnitude of mean differences. This is usually calculated after rejecting the null hypothesis in a statistical test. If the null hypothesis is not rejected, effect size has little meaning.

Statistics - Lecture 68: z-Test For Proportions, Two Samples

Researchers want to test the effectiveness of a new anti-anxiety medication. In clinical testing, 64 out of 200 people taking the medication report symptoms of anxiety. Of the people receiving a placebo, 92 out of 200 report symptoms of anxiety. Is the medication working any differently than the placebo?
Test this clain using alpha = 0.05

  1. Define Null and Alternative Hypotheses
  2. State Alpha
  3. State Decision Rule
  4. Calculate Test Statistic
  5. State Results
  6. State Conclusion

Statistics - Lecture 69: Confidence Intervals For The Difference Of Two Proportions

We use the z-Test for Proportions to test if two proportions are different from one another.

Statistics Lecture Series - Table Of Contents

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