Lulu Hypermarket has a record showing data on sales per year (in thousands of rials) and advertisement (in hundreds of rials) for the last five years. The record gives the following details. ΣΧ132 Σχ3,502 ΣΥ- 96 ΣΥ-1,870 ΣΧΥ-2,553 a. Please develop the least squares estimated regression line. b. Using your regression line developed in Part a, predict the sales when advertisement is $3,000. c. At a = 0.05, determine if advertisement and sales are related (perform at test).
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- An owner of a home in the Midwest installed solar panels to reduce heating costs. After installing the solar panels, he measured the amount of natural gas used y (in cubic feet) to heat the home and outside temperature x (in degree-days, where a day's degree-days are the number of degrees its average temperature falls below 65° F) over a 23-month period. He then computed the least-squares regression line for predicting y from x and found it to be ŷ = 85 + 16x. The software used to compute the least-squares regression line for the equation above says that r2 = 0.98. This suggests which of the following? 1. Gas used increases by square root of 0.98 = 0.99 cubic feet for each additional degree-day? 2. Although degree-days and gas used are correlated, degree-days do not predict gas used very accurately. 3. Prediction of gas used from degree-days will be quite accurate.A regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The least squares regression line is weight = -5.94 + 0.1875 length. Explain in words what this model means (slop and intercept) The new- born boy was 48 cm long, what is the predicted weight of this boy? It is known that the boy is weighed 3 kg. what was his residual? What does that say about him?A pediatrician wants to determine the relationship that exists between achild’s height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and conducts the least-squares regression analysis with the simple linear model using StatCrunch. The output is given below: (a) Write down the equation of the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. (b) Interpret the slope and y-intercept, if appropriate. (c) Use the regression equation to predict the head circumference of a child who is 25 inches tall. Assume that the regression model is applicable.(d) It is observed that one child who is 25 inches tall has a head circumference of 17.5 inches. Is the observed value above or below average among all children with heights of 25 inches?
- A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. Assuming a linear relationship, use the least-squares method to determine the regression coefficients b0 and b1. Interpret the meaning of the slope, b1, in this problem. Predict the mean opening weekend box office gross for a movie that had 80 million online trailer views. What insights can be obtained about predicting opening weekend box office gross from online trailer views?An owner of a home in the Midwest installed solar panels to reduce heating costs. After installing the solar panels, he measured the amount of natural gas use y (in cubic feet) to heat the home and outside temperature x (in degree-days, where a day’s degree-days are the number of degrees its average temperature falls below 65F) over a 23-month period. He then computed the least squares regression line for predicting y from x and found it to be, ŷ=85+16x How much, on average, does gas used increase for each additional degree-day? The predicted amount of gas used when the outside temperature is 20 degree- days.A researcher at a large company has collected data on the beginning salary and current salary of 48 randomly selected employees. The least-squares regression equation for predicting their current salary from theirbeginning salary isY = -2500 + 2.1X Where Y is the current salary, and X is the beginning salary.Jay started working for the company earning $ 30,000. He currently earns $60,000. What is the residual for Jay (assuming no extrapolation error)? Please show calculations
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- A company that holds the DVD distribution rights to movies previously released only in theaters wants to estimate sales revenue of DVDs based on box office success. The box office gross (in Php millions) for each of 22 movies in the year that they were released and the DVD revenue (in Php millions) in the following year are shown below and stored in a. construct a scatter plot. b. assuming a linear relationship, use the least-squares method to determine the regression coefficients b0 and b c. interpret the meaning of the slope, in this problem d. predict the sales revenue for a movie DVD that had a box office gross of Php75 million..1The data regarding the production of wheat in tons (X) and the price of the kilo of flour in Ghana cedis (Y) Takoradi some years ago were: a. Fit the regression line for the day using the method of least squaresA least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight=−5.82+0.1601 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?