A simple random sample of size n = 15 is drawn from a population that is normally distributed. The sample variance is found to be 23.8. Determine whether the population variance is less than 25 at the α = 0.01 level of significance.
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
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Means
Problem 10.3.5a
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.
a. If x̄ = 104.8 and s = 9.2, compute the test statistic.
b. If the researcher decides to test this hypothesis at the α = 0.01 level of significance, determine the critical values.
Verified step by step guidance1
Identify the null hypothesis \(H_0: \mu = 100\) and the alternative hypothesis \(H_1: \mu \neq 100\). Since the population is normally distributed and the sample size is \(n = 23\), we will use a t-test for the mean.
Calculate the test statistic using the formula for the one-sample t-test:
\[ t = \frac{\overline{x} - \mu_0}{s / \sqrt{n}} \]
where \(\overline{x} = 104.8\), \(\mu_0 = 100\), \(s = 9.2\), and \(n = 23\).
Substitute the values into the formula to express the test statistic as:
\[ t = \frac{104.8 - 100}{9.2 / \sqrt{23}} \]
This will give the calculated t-value for the sample.
For part (b), determine the critical values for a two-tailed test at the significance level \(\alpha = 0.01\). Since the sample size is 23, the degrees of freedom are \(df = n - 1 = 22\).
Use the t-distribution table or a calculator to find the critical t-values \(t_{\alpha/2, df}\) and \(-t_{\alpha/2, df}\) corresponding to \(\alpha/2 = 0.005\) and \(df = 22\). These critical values define the rejection regions for the hypothesis test.
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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 calculating a test statistic from sample data and comparing it to critical values to determine significance.
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Performing Hypothesis Tests: Proportions
t-Distribution and Test Statistic
When the population standard deviation is unknown and the sample size is small, the test statistic follows a t-distribution. The test statistic is calculated as (sample mean - hypothesized mean) divided by the sample standard deviation over the square root of the sample size, reflecting how far the sample mean deviates from the null hypothesis.
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Step 2: Calculate Test Statistic
Critical Values and Significance Level
Critical values define the cutoff points beyond which the null hypothesis is rejected. They depend on the chosen significance level (α) and the degrees of freedom. For a two-tailed test at α = 0.01, critical values are the t-values that correspond to the upper and lower 0.5% tails of the t-distribution.
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