The notation tα is the t-value such that the area under the t-distribution to the right of tα is .
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 57m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
7. Sampling Distributions & Confidence Intervals: Mean
Sampling Distribution of the Sample Mean and Central Limit Theorem
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
A company’s marketing team takes 50 samples of 10 recent clients to create a sampling distribution of sample means for the average amount spent per month on company products. Can the Central Limit Theorem be used to determine that the sampling distribution is normal?
A
No
B
Yes
C
More information is required
Verified step by step guidance1
Understand the Central Limit Theorem (CLT): The CLT states that the sampling distribution of the sample mean will be approximately normal if the sample size is sufficiently large (typically n ≥ 30) or if the population itself is normally distributed.
Identify the given information: The problem states that 50 samples of size 10 are taken, but it does not provide information about the shape of the population distribution or whether the population is normal.
Evaluate the sample size: Since the sample size is 10, which is less than 30, the CLT cannot guarantee that the sampling distribution of the sample mean will be normal unless the population itself is normal.
Determine if more information is needed: To conclude whether the sampling distribution is normal, we need to know if the population distribution is normal. This information is not provided in the problem.
Conclude: Based on the lack of information about the population distribution, the correct answer is 'More information is required.'
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