14.57.161.421.049.725.365.826.944.3Send data to calculatorSend data to Excel3.13.610.05.716.19.19.311.37.8Based on the studio's data and the regression line, complete the following.Rental reve(in millions ofXXXTheater revenue(in millions of dollars)(a) For these data, values for theater revenue that are less than the mean of the values for theater revenue tend to bepaired with values for rental revenue that are (Choose one) ▼ the mean of the values for rental revenue.greater thanless than(b) According to the regression equation, for an increase Ur une mmion donars in theater revenue, there is acorresponding increase of how many million dollars in rental revenue?06070SEspañol€DAs Can movie rental revenue be predicted?A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from thetheatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These datagive the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteenmovies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is y= 3.84 +0.14x.Theater revenue, x(in millions of dollars)30.760.625.428.436.513.214.57.161.421.049.725.365.826.944.3Send data to calculatorVRental revenue, y(in millions of dollars)Send data to Excel4.616.16.62.812.410.23.13.610.05.716.19.19.311.37.8Rental revenue(in millions of dollars)18-16+14+12+10-816.010*xх х26 36 40Theater revenue(in millions of dollars)EspanolD1AaM?

Given information: y^=3.84+0.14·x Theater revenue(x) Rental revenue(y) 30.7 4.6 60.6 16.1…

Answered: 14.5 7.1 61.4 21.0 49.7 25.3 65.8 26.9…

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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KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
The following table shows the reported net sales by Nokia in 2008, 2009, and 2010. Year 2008 2009 2010x 0 1 2Sales ($ millions) 20 50 60 Find the Equation of the Linear Regression Line. Rounds decimal values to the nearest tenths.
Suppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 9 9 11 10 11 14 4 13 7 6 y 7.59 6.87 13.06 7.32 8.58 6.09 5.62 8.35 6.73 7.77 5.9 Create a scatterplot of the data. Choose the correct graph below. O A. OB. OC. Oc. OD. Ay 25- Ay 25- Ay 25- 25- 20 20- 20- 20- 155 155 155 155 105 105 105 105 5- 55 55 55 0- Ó 5 10 15 20 25 0- 0- 05 10 15 20 25 Ó 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. The data has a pattern that is not a straight line. O B. There is no characteristic of the data that is ignored by the regression line. OC. There is an influential point that strongly affects the graph of the regression line. O D. There is no trend in the data.
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft.The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained:The regression equation is ????? = ? + ???????? + ?????? ???? + ???? ????Predictor Coef SE Coef T PConstant 37718 14177 2.66 **Bedrooms 2306 6994 0.33 0.742House Size 74.3 52.98 * 0.164Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF SS MS F PRegression 3 76501718347 25500572782 *** ****Residual…
It is inferred that the tip amount has a relationship with value of a dinner bill. The collected data is presented in the table. Conduct a regression analysis. X - Bill ($) 33.46 50.68 87.92 98.84 63.60 107.34 Y - Tip ($) 5.70 5.00 8.08 17.00 12.00 16.00
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 8 11 13 6 13 6 y 7.24 6.87 12.78 6.87 7.75 8.85 6.28 5.61 8.28 6.72 5.52 Create a scatterplot of the data. Choose the correct graph below. VA. OB. OC. OD. 25- Ay 25- 25- 25- 20- 20 20- 20 15 155 155 155 10- 10- 10 10- 5- 5- 5 55 0- 05 10 15 20 25 0- O 5 10 15 20 25 04 05 10 15 20 25 0- 05 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.)
1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained:The regression equation is ????? = ? + ???????? + ?????? ???? + ???? ????Predictor Coef SE Coef T PConstant 37718 14177 2.66 **Bedrooms 2306 6994 0.33 0.742House Size 74.3 52.98 * 0.164Lot Size -4.36 17.02 -0.26 0.798S= 25023 R-Sq=56.0% R-Sq(adj)=54.6%Source DF SS MS F PRegression 3 76501718347 25500572782 *** ****Residual Error 96 60109046053 626135896Total 99a) Write out the regression equation. b) Fill in the missing values *, **, *** and ****. c) Use the p-value approach to determine if ? is significant at the 5% significance leveld) Is ? significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term “R-sq” and…
Run the Linear Regression Analysis for the following: → Submit Excel FileThe average driving distance (yards) and driving accuracy (percent of drives that land in thefairway) for 8 golfers are recorded in the table below.Rank Driving Distance (yards) Driving Accuracy (%)1 316.3 41.72 304.9 48.83 310.8 42.34 312.5 41.25 294.5 54.76 290.7 54.47 296.9 54.28 295.6 53.9a- Write the equation of a straight-line model relating driving accuracy (y) to drivingdistance (x). Select one of the following:i. Y = β1x + εii. Y = β1x2+ β0iii. Y = β1xiv. Y = β0 + β1x + εb- Fit the model and give the least square prediction equation c- Interpret the estimated y-intercept of the line. Choose the correct answer below:i. Since a drive with 0% accuracy is outside the range of the sample data, the y-intercepthas no practical interpretation.ii. Since a drive with distance 0 yards is outside the range of the sample data, the y-intercept has no practical interpretation.iii. For…
5. Explain what the correlation coefficient tells you about the relationship between your variables. 7. Interpret the slope of the regression equation in terms of the variables in your data set.
derwin

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