Two random independent groups are exposed to different stimuli. The mean outcomes for these two groups differ. This video will provide examples of the types of issues these techniques can address.
- Consider this situation,…a large national corporation…has a hundred senior executives.…About 40 of those senior executives are women.…The other 60 are men.…It is found that the average salary…for male senior executives…is about $15,000 per year greater…than the salaries of the female senior executives.…Why are male senior executives at this company…paid higher salaries?…Does the gender of the senior executives play a role?…Let's take a look at another scenario.…
A hundred obese males in their 20s are randomly assigned…to two groups for a period of three months.…One group of males exercise two hours a day…but are allowed to eat whatever they please.…The other group of males are not required to exercise,…but they must adhere to a very strict diet.…The males on the strict diet…lose an average of four pounds more…during the three month period versus the individuals…that are required to exercise two hours per day.…
Is diet a better mechanism for influencing weight loss…among young obese males versus daily exercise?…
- Working with small sample sizes
- Using t-statistic vs. z-statistic
- Calculating confidence intervals with t-scores
- Comparing two populations (proportions)
- Comparing two population means
- Chi-square testing
- ANOVA testing
- Regression testing
Skill Level Advanced
1. The Statistics Series: A Look Back and Forward
2. Small Sample Sizes
T-statistic vs. z-statistic3m 44s
3. Comparing Two Populations (Proportions)
4. Comparing Two Populations (Means)
6. ANOVA: Analysis of Variance
7. Introduction to Regression
Next steps1m 40s
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