Regression Stats

Regression Stats

Question 1 1 pts

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0numerical_question 77939220

<p>Find the y-intercept of the equation of the regression line for the following data:</p>_x000D_<br /> <table border=”0″>_x000D_<br /> <tbody>_x000D_<br /> <tr>_x000D_<br /> <td>Consumer Price Index</td>_x000D_<br /> <td>30.2</td>_x000D_<br /> <td>48.3</td>_x000D_<br /> <td>112.3</td>_x000D_<br /> <td>162.2</td>_x000D_<br /> <td>191.9</td>_x000D_<br /> <td>197.8</td>_x000D_<br /> </tr>_x000D_<br /> <tr>_x000D_<br /> <td>Cost of Pizza</td>_x000D_<br /> <td>0.15</td>_x000D_<br /> <td>0.35</td>_x000D_<br /> <td>1.00</td>_x000D_<br /> <td>1.25</td>_x000D_<br /> <td>1.75</td>_x000D_<br /> <td>2.00</td>_x000D_<br /> </tr>_x000D_<br /> </tbody>_x000D_<br /> </table>_x000D_<br /> <p> </p>_x000D_<br /> <p>Please round to the nearest thousandth. </p>_x000D_<br /> <p> </p>_x000D_<br /> <p> </p>_x000D_<br />

Find the y-intercept of the equation of the regression line for the following data:

Consumer Price Index	30.2	48.3	112.3	162.2	191.9	197.8
Cost of Pizza	0.15	0.35	1.00	1.25	1.75	2.00

Please round to the nearest thousandth.

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Question 2 1 pts

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<p>Find the slope of the equation of the regression line for the following data:</p>_x000D_<br /> <table border=”0″>_x000D_<br /> <tbody>_x000D_<br /> <tr>_x000D_<br /> <td>Consumer Price Index</td>_x000D_<br /> <td>30.2</td>_x000D_<br /> <td>48.3</td>_x000D_<br /> <td>112.3</td>_x000D_<br /> <td>162.2</td>_x000D_<br /> <td>191.9</td>_x000D_<br /> <td>197.8</td>_x000D_<br /> </tr>_x000D_<br /> <tr>_x000D_<br /> <td>Cost of Pizza</td>_x000D_<br /> <td>0.15</td>_x000D_<br /> <td>0.35</td>_x000D_<br /> <td>1.00</td>_x000D_<br /> <td>1.25</td>_x000D_<br /> <td>1.75</td>_x000D_<br /> <td>2.00</td>_x000D_<br /> </tr>_x000D_<br /> </tbody>_x000D_<br /> </table>_x000D_<br /> <p> </p>_x000D_<br /> <p>Please give your answers rounded to the nearest hundredth..</p>_x000D_<br /> <p> </p>_x000D_<br />

Find the slope of the equation of the regression line for the following data:

Consumer Price Index	30.2	48.3	112.3	162.2	191.9	197.8
Cost of Pizza	0.15	0.35	1.00	1.25	1.75	2.00

Please give your answers rounded to the nearest hundredth..

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Question 3 1 pts

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<p>For a certain set of data, the Pearson correlation coefficient was 0.87. It was calculated based on 50 data points. Answer the following questions, based off of this information.</p>_x000D_<br /> <p>(a) Let alpha be 0.05. Is the correlation coefficient significant? <select class=’question_input’ name=’question_40020817_15079212678389be90607b4f519dafb8′>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’44592′>Yes</option>”, “<option value=’32329′>No</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br /> <p>(b) Using your answer from (a), is it reasonable to fit the regression line to the data? <select class=’question_input’ name=’question_40020817_b11445f111fcead904fdb75050743c6c’>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’88754′>Yes</option>”, “<option value=’60974′>No</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br /> <p>(c) If you were to the predict a value of the dependent variable, would you use the regression line or the mean of all the values of the dependent variable? <select class=’question_input’ name=’question_40020817_e7150e909f975f89602363f66f6b3179′>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’31050′>Regression line</option>”, “<option value=’77605′>Mean of all the values of the dependent variable</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br />

For a certain set of data, the Pearson correlation coefficient was 0.87. It was calculated based on 50 data points. Answer the following questions, based off of this information.

(a) Let alpha be 0.05. Is the correlation coefficient significant? [ Select ] [“Yes“, “No“]

(b) Using your answer from (a), is it reasonable to fit the regression line to the data? [ Select ] [“Yes“, “No“]

(c) If you were to the predict a value of the dependent variable, would you use the regression line or the mean of all the values of the dependent variable? [ Select ] [“Regression line“, “Mean of all the values of the dependent variable“]

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Question 4 1 pts

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<p>For a certain set of data, the Pearson correlation coefficient was -0.467. It was calculated based on 8 data points. Answer the following questions, based off of this information.</p>_x000D_<br /> <p>(a) Let alpha be 0.05. Is the correlation coefficient significant? <select class=’question_input’ name=’question_40020818_15079212678389be90607b4f519dafb8′>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’1283′>Yes</option>”, “<option value=’8678′>No</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br /> <p>(b) Using your answer from (a), is it reasonable to fit the regression line to the data? <select class=’question_input’ name=’question_40020818_b11445f111fcead904fdb75050743c6c’>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’44432′>Yes</option>”, “<option value=’5855′>No</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br /> <p>(c) If you were to the predict a value of the dependent variable, would you use the regression line or the mean of all the values of the dependent variable? <select class=’question_input’ name=’question_40020818_e7150e909f975f89602363f66f6b3179′>_x000D_<br /> <option value=”>_x000D_<br /> [ Select ]_x000D_<br /> </option>_x000D_<br /> [“<option value=’64248′>Regression Line</option>”, “<option value=’24732′>Mean of all of the values of the dependent variable</option>”]_x000D_<br /> </select>_x000D_<br /> </p>_x000D_<br />

For a certain set of data, the Pearson correlation coefficient was -0.467. It was calculated based on 8 data points. Answer the following questions, based off of this information.

(a) Let alpha be 0.05. Is the correlation coefficient significant? [ Select ] [“Yes“, “No“]

(b) Using your answer from (a), is it reasonable to fit the regression line to the data? [ Select ] [“Yes“, “No“]

(c) If you were to the predict a value of the dependent variable, would you use the regression line or the mean of all the values of the dependent variable? [ Select ] [“Regression Line“, “Mean of all of the values of the dependent variable“]

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Question 5 1 pts

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0numerical_question 77939221

In a study conducted by University of Arizona researchers, the total weight (in pounds) of garbage discarded in one week and the household size were recorded for 62 households. The linear correlation coefficient is r = 0.759 and the regression equation is <img class=”equation_image” title=”hat{y}” src=”/equation_images/%255Chat%257By%257D” alt=”hat{y}”>= 0.445 + 0.119x, where x represents the total weight of discarded garbage. The mean of the 62 garbage weights is 27.4 pounds and the 62 households have a mean size of 3.71 people. What is the best predicted number of people in a household that discards 50 pounds of garbage? Round to the nearest hundredth.

In a study conducted by University of Arizona researchers, the total weight (in pounds) of garbage discarded in one week and the household size were recorded for 62 households. The linear correlation coefficient is r = 0.759 and the regression equation is
$\hat{y}$= 0.445 + 0.119x, where x represents the total weight of discarded garbage. The mean of the 62 garbage weights is 27.4 pounds and the 62 households have a mean size of 3.71 people. What is the best predicted number of people in a household that discards 50 pounds of garbage? Round to the nearest hundredth.

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Question 6 1 pts

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A sample of 40 women is obtained, and their heights (in inches) and pulse rates (in beats per minutes) are measured. The linear correlation coefficient is 0.202 and the equation of the regression line is <img class=”equation_image” title=”hat{y}” src=”/equation_images/%255Chat%257By%257D” alt=”hat{y}”>= 18.2 + 0.920x, where x represents height (based on data from the National Health Examination Survey). The mean of the 40 heights is 63.2 in. and the mean of the 40 pulse rates is 76.3 beats per minute. Find the best predicted pulse rate of a woman who is 70 inches tall. Please round to the nearest tenth.

A sample of 40 women is obtained, and their heights (in inches) and pulse rates (in beats per minutes) are measured. The linear correlation coefficient is 0.202 and the equation of the regression line is
$\hat{y}$= 18.2 + 0.920x, where x represents height (based on data from the National Health Examination Survey). The mean of the 40 heights is 63.2 in. and the mean of the 40 pulse rates is 76.3 beats per minute. Find the best predicted pulse rate of a woman who is 70 inches tall. Please round to the nearest tenth.