The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend Interpret the y-intercept of the regression line in context.

The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend Interpret the y-intercept of the regression line in context.

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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The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend (ii) Use the regression equation to calculate the predicted total world gross ticket sales for a movie with opening weekend ticket sales of 90 (millions of $US). Give your answer to 2 decimal places (2dp). (millions of $US)
Canada's trade balance with the rest of the world has been steadily increasing over the past several years. It is well known that the U.S. is Canada's leading trade partner. Is there a predictable linear relationship between our total trade balance and our trade balance with the U.S.? Develop a regression model to predict the trade balance with the U.S. by our trade balance with the rest of the world. Comment on the strength of the model. Develop a time-series trend line for trade balance with the rest of the world by using the time periods given. Forecast total trade balance with the rest of the world for 2020 using this equation. Trade Balance ($ millions) Year Rest of the World U.S. 2010 2,290 4,991 2011 2,486 4,709 2012 2,776 4,641 2013 2,648 5,220 2014 3,068 5,041 2015 3,688 4,750 2016 4,111 4,321 2017 4,172 4,699 2018 3,669 4,777 2019 3,493 4,809 question 1: y̅ = ?+?x question…
You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are: I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars. Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.
The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend (iv) Interpret the slope of the regression line in context.
write the regression equation that will predict the number of manatees killed given thenumber of powerboat registrations (in 1000's). Show all work usingformulas for slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. Show all the calculations and math of slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. SHOW ALL WORK! DO NOT USE EXCEL! I need to be able to see every single part and how you got it. attached is the question
Data was collected for a regression analysis where sleep quality (as a percentage) depends on the amount of caffeine consumed in a day (measured in mg). bo was found to be 92.7, b₁ was found to be -0.76, and R² was found to be 0.86. Interpret the slope of the line. O On average, each one mg increase in caffeine consumed increases a person's sleep quality by 92.7%. O On average, when x = = 0, a person has a sleep quality of -0.76%. O On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%. On average, when x = 0, a person has a sleep quality of 92.7%. O We should not interpret the slope in this problem. O We should interpret the slope in this problem, but none of the above are correct.
The linear regression equation for the data from the number 2 is y=.27x+5.82. Describe the slope of the linear best-fit equations.
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) = 109 + 0.2*SM_DOLLARS + 1.5*RADIO_ADS + 1.1*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 $150 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 + 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.)
Data was collected for a regression analysis where sleep quality (as a percentage) depends on the amount of caffeine consumed in a day (measured in mg). bo was found to be 92.7, bị was found to be -0.76, and R' was found to be 0.86. Interpret the slope of the line. On average, each one mg increase in caffeine consumed increases a person's sleep quality by 92.7%. On average, when x = 0, a person has a sleep quality of -0.76%. On average, when x = 0, a person has a sleep quality of 92.7%. On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%. We should not interpret the slope in this problem. We should interpret the slope in this problem, but none of the above are correct.
The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend Is the interpretation for the y-intercept meaningful in this context? Explain your answer in one or two sentences.
Can the regression equation reasonably be used to make predictions