Tue MPreviewFileEditViewGoToolsWindow HelpO IMG 2729 ing.A O.IMG 2724.jpg® Q Q Ûe- O @ Qr SearchO-Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in °F. Find the regression equation, letting chirps in 1 minute be theindependent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrongwith this predicted temperature?Chirps in 1 min1050 120583277012429461056 1110 OTemperature (°F)79.4 93.469.8 70.193.680.5 83.5 89.1ListedaudIstesamUsebetwThe regression equation is y =+(x.(Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.)minuIn thThe best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, based on the regression equation, is1°F.(Typ(Round to the nearest integer as needed.)Iden1- What is wrong with this predicted temperature?IdenO A. It is only an approximation. An unrounded value would be considered accurate.P-vaWhaOB. The chirps in 1 minute should have been the dependent variable.SindtherOC. It is unrealistically high. The value 3000 is far outside of the range of observed values.O D. Nothing is wrong with this value. It can be treated as an accurate prediction.25013 MAY3MacBook Air

Use EXCEL to determine the regression equation. EXCEL procedure: Go to EXCEL Go to Data>Data…

Answered: Listed below are the numbers of cricket…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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Please answer all sections
Excel file: https://drive.google.com/file/d/1TQG5r2wzLGk--75whZXyb0SDTHZTWS0S/view?usp=sharing
Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in °F. Find the regression equation, letting chirps in 1 minute be the independent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Use a significance level of 0.05. Chirps in 1 min Temperature (°F) 1149 1040 887 1081 1191 781 788 84.7 80.4 72.7 85.9 94.3 66.9 788 O 73.8 70.6 The regression equation is y = + (x. (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.) The best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, based on the regression equation, is (Round to the nearest integer as needed.) What is wrong with this predicted temperature? OA. It is unrealistically high. The value 3000 is far outside of the range of observed values. OB. It is only an approximation. An…
make a regression analysis about any healthcare issue
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.5*SM_DOLLARS + 0.5*RADIO_ADS + 0.8*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $108 without changing the amount spent on radio ads or web search ads? (Round your answer to the nearest whole number.)
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 0.75*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $220 without changing the amount spent on radio ads or web search ads? (Round your answer to the nearest whole number.) Based on the…
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…
Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.4mm. How does the result compare to the actual height of 1776mm ? \table[[Foot Length,281.6, 278.0, 252.9, 258.8, 279.2, 257.8, 273.9, 261.6],[ Height, 1785.4, 1771.0, 1676.1, 1645.8, 1859.2, 1710.3, 1788.7, 1737.3]] The regression equation is hat(y) = +1, (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) ა C Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 273.4 mm. How does the result compare to the actual height of 1776 mm? Foot Length 281.6 278.0 252.9 258.8 279.2 257.8 273.9 261.6 Height 1785.4 1771.0 1676.1 1645.8 1859.2 1710.3 1788.7 1737.3 The regression…
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right am blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 100 mm Hg Use a significance level of 0.05. Right Arm 103 102 95 78 Left Arm 175 169 147 146 144 m Click the icon to view the critical values of the Pearson correlation coetticient r The regression oquation is y =+O (Round to one decimal place as needed) Given that the systolic blood pressure in the right arm is 100 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg (Round to one decimal place as needed.)
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05. Right Arm 100 99 91 76 Left Arm 175 170 146 147 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y=+x. (Round to one decimal place as needed.) % 5 Given that the systolic blood pressure in the right arm is 85 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.) Submit test Copyright © 2022 Pearson Education Inc. All rights reserved. Terms of Use | Privacy Policy Permissions Contact Us 6: 6 G H 8 4- 7 B N a hp 8 76 146 JK M H N (?) 83°F 12 + [ insert see score past due see score 40) 10:26 PM 8/9/2022 prt sc…

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