A simple random sample of size n = 19 is drawn from a population that is normally distributed. The sample mean is found to be 0.8, and the sample standard deviation is found to be 0.4. Test whether the population mean is less than 1.0 at the α = 0.01 level of significance.
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- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 17m
- 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 - ExcelBonus23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - ExcelBonus28m
- Confidence Intervals for Population Means - ExcelBonus25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - ExcelBonus12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - ExcelBonus9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - ExcelBonus21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - ExcelBonus12m
- Two Variances and F Distribution29m
- Two Variances - Graphing CalculatorBonus16m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - ExcelBonus8m
- Finding Residuals and Creating Residual Plots - ExcelBonus11m
- Inferences for Slope31m
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- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression15m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 29m
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Means
Problem 10.3.5e
Textbook Question
To test H0: μ = 100 versus H1: μ ≠ 100, a simple random sample of size n = 23 is obtained from a population that is known to be normally distributed.
e. Construct a 99% confidence interval to test the hypothesis.
Verified step by step guidance1
Identify the sample size \(n = 23\) and the population is normally distributed, which allows us to use the \(t\)-distribution for inference since the population standard deviation is unknown.
Determine the confidence level, which is 99%, so the significance level \(\alpha = 1 - 0.99 = 0.01\). Since this is a two-tailed test, split \(\alpha\) into two tails: \(\alpha/2 = 0.005\).
Find the critical value \(t_{\alpha/2, n-1}\) from the \(t\)-distribution table with degrees of freedom \(df = n - 1 = 22\) and tail probability \$0.005$.
Calculate the sample mean \(\bar{x}\) and the sample standard deviation \(s\) from the data (these values should be given or calculated from the sample).
Construct the 99% confidence interval for the population mean \(\mu\) using the formula:
\(\displaystyle \bar{x} \pm t_{\alpha/2, n-1} \times \frac{s}{\sqrt{n}}\)
This interval will help you test the hypothesis by checking if 100 lies within this interval.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Hypothesis Testing
Hypothesis testing is a statistical method used to decide whether there is enough evidence to reject a null hypothesis (H0) in favor of an alternative hypothesis (H1). It involves comparing sample data against a hypothesized population parameter, using significance levels to control error rates.
Recommended video:
Performing Hypothesis Tests: Proportions
Confidence Interval
A confidence interval estimates a range of values within which the true population parameter is likely to fall, with a specified level of confidence (e.g., 99%). It provides an interval estimate rather than a single point, reflecting the uncertainty inherent in sampling.
Recommended video:
Introduction to Confidence Intervals
t-Distribution and Small Sample Inference
When the sample size is small (n < 30) and the population standard deviation is unknown, the t-distribution is used instead of the normal distribution. It accounts for extra variability and is essential for constructing accurate confidence intervals and hypothesis tests with small samples.
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Sampling Distribution of Sample Proportion
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