If and , find the probability of getting a sample mean above 3.5 in a sample of 60 people.
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically2h 8m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables3h 28m
- 6. Normal Distribution & Continuous Random Variables2h 21m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 37m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals22m
- Confidence Intervals for Population Mean1h 26m
- 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 33m
- 9. Hypothesis Testing for One Sample3h 32m
- 10. Hypothesis Testing for Two Samples4h 49m
- Two Proportions1h 12m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 2m
- 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 59m
- 13. Chi-Square Tests & Goodness of Fit2h 31m
- 14. ANOVA2h 1m
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 sample size: In this problem, the sample size is 10 (n = 10), which is less than 30. This means the sample size alone does not guarantee that the sampling distribution will be normal.
Consider the population distribution: To apply the CLT for smaller sample sizes, the population distribution must be normal. However, the problem does not provide information about the shape of the population distribution.
Evaluate the given options: Since the sample size is small and the population distribution is unknown, we cannot definitively determine whether the sampling distribution is normal.
Conclude: The correct answer is 'More information is required' because we need additional details about the population distribution to apply the CLT in this scenario.
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Sampling Distribution of the Sample Mean and Central Limit Theorem practice set

