Statistics Lectures - 22: More Samples t-Test

Related Pages
20: One Sample z-Test & One Sample t-Test
21: Various Types Of Samples t-Test
23: ANOVA
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

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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.

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Statistics Lecture Series - Table Of Contents

• Descriptive Statistics
• Probability
• Correlation
• Inferential Statistics

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