Let's combine our knowledge of degrees of freedom, t-score tables, small sample sizes, and the approximate standard error to develop confidence intervals.
- Let's develop a confidence interval using t scores.…Remember, that this confidence interval…gives us a range of values…for estimated population parameter.…Imagine that a national testing organization…has made some major changes to the standardized exam…that most aspiring college students take.…The exam scores range between 50 points and 200 points.…The old exam typically had an average score of 130 points.…
They like to see how the average score…for the updated exam compares…to the old version of the exam.…Further, this testing organization…wants to create a 98% confidence interval…for the updated exam's mean score.…In order to do so, they gave the updated test…to a random sample of 10 aspiring college students.…The scores for these 10 students are as follows.…Our sample mean is 126,…while we don't know the standard deviation…of the exam scores for the entire population…of aspiring college students,…we can calculate the standard deviation…for this sample, 29.51.…
We also know that since our sample size N was 10,…
- 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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