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Problem 4 (30 points) Amy is interested in moving to California but isn't certain which city she'd prefer. One variable of interest to her is the proportion of rainy days in each city. She took a random sample of days for each of the four biggest cities in California (Los Angeles, San Francisco, San Diego, and San Jose) and recorded the results. If a day contained any precipitation, it is considered a rainy day. Counts of days with and without rain in each of the four cities are summarized in the given StatKey output. 1. Find the two missing values in the StatKey output. Expected count for (Rain, SD) = Precipitation City LA SF SD SJ Total 4 6 22 3 Rain 5.6 5.2 5.2 35 0.462 0.137 0.45 0.904 No Rain Total 25 202 21 17 19.4 17.8 0.134 23 6 608 20 65.9 17.8 121 0.13 0.262 85 23 156 Observed, Expected, Contribution tox Contribution for (No Rain, SF) = 2. Are conditions met for using a x² distribution for a test of association? Explain specifically what you checked and list All the numbers that you checked. 3. Write in words (without using technical notation!) the appropriate null and alternative hypothesis to determine if the proportion of rainy days is different among these four cities. (Be careful! In your formulation you should use the word "different" or "difference".) Ho: Ha: 4. Calculate the test statistic and its degrees of freedom. x² = df= 5. Use Table B to estimate the P-value. P-value estimate: 6. Make a formal decision. Decision: Reject Ho Do not reject Ho Why you made this decision: 7. Conclude in context.

Problem 4 (30 points) Amy is interested in moving to California but isn't certain which city she'd prefer. One variable of interest to her is the proportion of rainy days in each city. She took a random sample of days for each of the four biggest cities in California (Los Angeles, San Francisco, San Diego, and San Jose) and recorded the results. If a day contained any precipitation, it is considered a rainy day. Counts of days with and without rain in each of the four cities are summarized in the given StatKey output. 1. Find the two missing values in the StatKey output. Expected count for (Rain, SD) = Precipitation City LA SF SD SJ Total 4 6 22 3 Rain 5.6 5.2 5.2 35 0.462 0.137 0.45 0.904 No Rain Total 25 202 21 17 19.4 17.8 0.134 23 6 608 20 65.9 17.8 121 0.13 0.262 85 23 156 Observed, Expected, Contribution tox Contribution for (No Rain, SF) = 2. Are conditions met for using a x² distribution for a test of association? Explain specifically what you checked and list All the numbers that you checked. 3. Write in words (without using technical notation!) the appropriate null and alternative hypothesis to determine if the proportion of rainy days is different among these four cities. (Be careful! In your formulation you should use the word "different" or "difference".) Ho: Ha: 4. Calculate the test statistic and its degrees of freedom. x² = df= 5. Use Table B to estimate the P-value. P-value estimate: 6. Make a formal decision. Decision: Reject Ho Do not reject Ho Why you made this decision: 7. Conclude in context.

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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Problem 4 (30 points) Amy is interested in moving to California but isn't certain which city she'd prefer. One variable of interest to her is the proportion of rainy days in each city. She took a random sample of days for each of the four biggest cities in California (Los Angeles, San Francisco, San Diego, and San Jose) and recorded the results. If a day contained any precipitation, it is considered a rainy day. Counts of days with and without rain in each of the four cities are summarized in the given StatKey output. 1. Find the two missing values in the StatKey output. Expected count for (Rain, SD) = Precipitation City LA SF SD SJ Total 4 6 22 3 Rain 5.6 5.2 5.2 35 0.462 0.137 0.45 0.904 No Rain Total 25 202 21 17 19.4 17.8 0.134 23 6 608 20 65.9 17.8 121 0.13 0.262 85 23 156 Observed, Expected, Contribution tox Contribution for (No Rain, SF) = 2. Are conditions met for using a x² distribution for a test of association? Explain specifically what you checked and list All the numbers that you checked. 3. Write in words (without using technical notation!) the appropriate null and alternative hypothesis to determine if the proportion of rainy days is different among these four cities. (Be careful! In your formulation you should use the word "different" or "difference".) Ho: Ha: 4. Calculate the test statistic and its degrees of freedom. x² = df= 5. Use Table B to estimate the P-value. P-value estimate: 6. Make a formal decision. Decision: Reject Ho Do not reject Ho Why you made this decision: 7. Conclude in context.
Transcribed Image Text:Problem 4 (30 points) Amy is interested in moving to California but isn't certain which city she'd prefer. One variable of interest to her is the proportion of rainy days in each city. She took a random sample of days for each of the four biggest cities in California (Los Angeles, San Francisco, San Diego, and San Jose) and recorded the results. If a day contained any precipitation, it is considered a rainy day. Counts of days with and without rain in each of the four cities are summarized in the given StatKey output. 1. Find the two missing values in the StatKey output. Expected count for (Rain, SD) = Precipitation City LA SF SD SJ Total 4 6 22 3 Rain 5.6 5.2 5.2 35 0.462 0.137 0.45 0.904 No Rain Total 25 202 21 17 19.4 17.8 0.134 23 6 608 20 65.9 17.8 121 0.13 0.262 85 23 156 Observed, Expected, Contribution tox Contribution for (No Rain, SF) = 2. Are conditions met for using a x² distribution for a test of association? Explain specifically what you checked and list All the numbers that you checked. 3. Write in words (without using technical notation!) the appropriate null and alternative hypothesis to determine if the proportion of rainy days is different among these four cities. (Be careful! In your formulation you should use the word "different" or "difference".) Ho: Ha: 4. Calculate the test statistic and its degrees of freedom. x² = df= 5. Use Table B to estimate the P-value. P-value estimate: 6. Make a formal decision. Decision: Reject Ho Do not reject Ho Why you made this decision: 7. Conclude in context.
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