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DO NOT ROUND YOUR ANSWERS!! SHOW ALL DECIMAL PLACES!! 1. Select Analysis, then Hypothesis Testing. Choose Proportion One Sample. Test the claim that the population proportion of successes equals 0.5. There were 100 observations and 61 of them were successes. Repeat the test for each significance level. Significance Level 0.05 0.01

DO NOT ROUND YOUR ANSWERS!! SHOW ALL DECIMAL PLACES!! 1. Select Analysis, then Hypothesis Testing. Choose Proportion One Sample. Test the claim that the population proportion of successes equals 0.5. There were 100 observations and 61 of them were successes. Repeat the test for each significance level. Significance Level 0.05 0.01

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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### Linear Regression and Hypothesis Testing #### Problem 3: Below is a table representing the weights and ages of bears: | Weight | 80 | 344 | 416 | 348 | 262 | 360 | 332 | 34 | |--------|-----|-----|-----|-----|-----|-----|-----|-----| | Age | 19 | 55 | 81 | 115 | 56 | 51 | 68 | 8 | Instructions: 1. Enter the values for Weight in column 1 and the values for Age in column 2. 2. Select Analysis, then Correlation and Regression. **Questions:** a) Find the equation of the regression line. ``` ______________________________________________________________________________________ ``` b) What is the best-predicted age of a bear that weighs 300 lbs? (Use your calculator) ``` ______________________________________________________________________________________ ``` #### Problem 4: Use a **0.01 significance level** to test the claim that the mean cotinine level is the same for the following three groups: 1. People who smoke (Smokers). 2. Nonsmokers who are exposed to “second-hand” smoke at home or work (ETS). 3. Nonsmokers not exposed to environmental tobacco smoke at home or work (NOETS). Instructions: 1. Click on Datasets, then Elementary Stats 11th Edition, then Passive and Active Smoke. 2. Select Analysis from the main menu, and then select One-Way Analysis of Variance. 3. Check # 1, 2, 3, and then click Evaluate. **Questions:** a) Critical F ``` ____________________________ ``` b) Test Statistic F: ``` ____________________________________________ ``` c) Initial Conclusion ``` ____________________________ ``` d) Final Conclusion ``` ____________________________________________ ``` This outline directs students on how to carry out a linear regression analysis and a one-way ANOVA test. The specific data and steps to follow ensure structured guidance for statistical analysis.
Transcribed Image Text:### Linear Regression and Hypothesis Testing #### Problem 3: Below is a table representing the weights and ages of bears: | Weight | 80 | 344 | 416 | 348 | 262 | 360 | 332 | 34 | |--------|-----|-----|-----|-----|-----|-----|-----|-----| | Age | 19 | 55 | 81 | 115 | 56 | 51 | 68 | 8 | Instructions: 1. Enter the values for Weight in column 1 and the values for Age in column 2. 2. Select Analysis, then Correlation and Regression. **Questions:** a) Find the equation of the regression line. ``` ______________________________________________________________________________________ ``` b) What is the best-predicted age of a bear that weighs 300 lbs? (Use your calculator) ``` ______________________________________________________________________________________ ``` #### Problem 4: Use a **0.01 significance level** to test the claim that the mean cotinine level is the same for the following three groups: 1. People who smoke (Smokers). 2. Nonsmokers who are exposed to “second-hand” smoke at home or work (ETS). 3. Nonsmokers not exposed to environmental tobacco smoke at home or work (NOETS). Instructions: 1. Click on Datasets, then Elementary Stats 11th Edition, then Passive and Active Smoke. 2. Select Analysis from the main menu, and then select One-Way Analysis of Variance. 3. Check # 1, 2, 3, and then click Evaluate. **Questions:** a) Critical F ``` ____________________________ ``` b) Test Statistic F: ``` ____________________________________________ ``` c) Initial Conclusion ``` ____________________________ ``` d) Final Conclusion ``` ____________________________________________ ``` This outline directs students on how to carry out a linear regression analysis and a one-way ANOVA test. The specific data and steps to follow ensure structured guidance for statistical analysis.
--- ### Math V44 – Computer 3 **Name: _____________________________________________** --- **DO NOT ROUND YOUR ANSWERS!! SHOW ALL DECIMAL PLACES!!** --- **1.** Select Analysis, then Hypothesis Testing. Choose Proportion One Sample. Test the claim that the population proportion of successes equals 0.5. There were 100 observations and 61 of them were successes. Repeat the test for each significance level. | Significance Level | 0.05 | 0.01 | |--------------------------|---------|---------| | Critical Values | | | | Test Statistic | | | | Initial Conclusion (H₀) | | | When the significance level is changed to a smaller value, the _______________ ________________ becomes larger or smaller (choose one) in absolute value. --- **2.** An instructor gives a test before and after a lesson. The results are: | Before | 42 | 47 | 53 | 37 | 61 | 88 | 45 | 50 | |------------|----|----|----|----|----|----|----|----| | After | 72 | 75 | 80 | 70 | 90 | 98 | 81 | 83 | Bring back the Sample Editor. Enter the Before values in column 1 and the After values in column 2. Select Analysis, then Hypothesis Testing, then Mean-Matched Pairs. At the 0.05 significance level, test the claim that the lesson has no effect on the test scores. a) Critical Values _________________________ b) Test Statistic __________________________ c) Initial Conclusion _______________________ d) Final Conclusion ________________________ --- This exercise involves conducting hypothesis tests to determine if there are significant changes or differences in specified conditions, such as population proportions and matched pairs before and after an intervention. Multiple significance levels are utilized to evaluate the robustness and validity of the initial conclusions versus the final conclusions.
Transcribed Image Text:--- ### Math V44 – Computer 3 **Name: _____________________________________________** --- **DO NOT ROUND YOUR ANSWERS!! SHOW ALL DECIMAL PLACES!!** --- **1.** Select Analysis, then Hypothesis Testing. Choose Proportion One Sample. Test the claim that the population proportion of successes equals 0.5. There were 100 observations and 61 of them were successes. Repeat the test for each significance level. | Significance Level | 0.05 | 0.01 | |--------------------------|---------|---------| | Critical Values | | | | Test Statistic | | | | Initial Conclusion (H₀) | | | When the significance level is changed to a smaller value, the _______________ ________________ becomes larger or smaller (choose one) in absolute value. --- **2.** An instructor gives a test before and after a lesson. The results are: | Before | 42 | 47 | 53 | 37 | 61 | 88 | 45 | 50 | |------------|----|----|----|----|----|----|----|----| | After | 72 | 75 | 80 | 70 | 90 | 98 | 81 | 83 | Bring back the Sample Editor. Enter the Before values in column 1 and the After values in column 2. Select Analysis, then Hypothesis Testing, then Mean-Matched Pairs. At the 0.05 significance level, test the claim that the lesson has no effect on the test scores. a) Critical Values _________________________ b) Test Statistic __________________________ c) Initial Conclusion _______________________ d) Final Conclusion ________________________ --- This exercise involves conducting hypothesis tests to determine if there are significant changes or differences in specified conditions, such as population proportions and matched pairs before and after an intervention. Multiple significance levels are utilized to evaluate the robustness and validity of the initial conclusions versus the final conclusions.
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