b. Determine the critical value for a left-tailed test of a population mean at the α = 0.01 level of significance based on a sample size of n = 40.
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
Steps in Hypothesis Testing
Problem 10.1.3
Textbook Question
If we reject the null hypothesis when the statement in the null hypothesis is true, we have made a Type ________ error.
Verified step by step guidance1
Understand the definition of a Type I error in hypothesis testing: it occurs when we reject the null hypothesis even though it is actually true.
Recall that the null hypothesis, denoted as \(H_0\), represents the default or status quo assumption in a statistical test.
Recognize that rejecting \(H_0\) when it is true means we have made an incorrect decision, specifically a Type I error.
Note that the probability of making a Type I error is denoted by \(\alpha\), which is also called the significance level of the test.
Therefore, the blank in the statement should be filled with 'I', indicating a Type I error.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Null Hypothesis
The null hypothesis is a default statement that there is no effect or no difference in a population. It serves as the starting assumption in hypothesis testing, and researchers seek evidence to either reject or fail to reject it based on sample data.
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Step 1: Write Hypotheses
Type I Error
A Type I error occurs when the null hypothesis is true, but we incorrectly reject it. This means we falsely detect an effect or difference that does not actually exist, often controlled by the significance level (alpha) in hypothesis testing.
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Types of Data
Hypothesis Testing Decision
Hypothesis testing involves making a decision to reject or fail to reject the null hypothesis based on sample evidence. Understanding the consequences of these decisions, including errors like Type I and Type II, is essential for interpreting test results correctly.
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Performing Hypothesis Tests: Proportions
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