Suppose data on advertising expenditures and revenue (both in thousands of dollars) for a certain restaurant follow.AdvertisingExpendituresRevenue1182324436.411052145355(a) Let x equal advertising expenditures (in thousands of dollars) and y equal revenue (in thousands of dollars). Use the method of least squares to develop a straight line approximation of therelationship between the two variables. (Round your numerical values to two decimal places.)(b) Test whether revenue and advertising expenditures (both in thousands of dollars) are related at a 0.05 level of significance. (Use the F test.)State the null and alternative hypotheses.Ho: B, 2 0Ha: P1 <0O Hoi B1= 0Ha: B1+ 0Ho: Po # 0= 0Ho: B1 + 0Ha: B1O Hoi PoHa: Po + 0= 020 Find the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.)p-valueState your conclusion.Reject Ho. We cannot conclude that the relationship between advertising expenditures and revenue (both in thousands of dollars) is significant.Do not reject Ho. We conclude that the relationship between advertising expenditures and revenue (both in thousands of dollars) is significant.Reject Ho. We conclude that the relationship between advertising expenditures and revenue (both in thousands of dollars) is significant.Do not reject Ho: We cannot conclude that the relationship between advertising expenditures and revenue (both in thousands of dollars) is significant.0.

The independent variable is Advertising Expenditures. The dependent variable is Revenue. This is…

Answered: Suppose data on advertising…

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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size (inches) 9 11 20 27 32 35 40 48 53 60 sale price (s) 147 186 197 297 447 1177 1228 1463 1650 17 h. What is the slope of the least-squares (best-fit) line? Interpret the slope.
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Q#5.(a) Given the following the values of the variables: Income (X) (000) 10 20 30 40 50 60 Expenditure(Y)(000) 7 21 23 34 6 53 Estimate the equation of least squares regression line and discuss your results. Estimate expenditure when Income is 70 and 80. Also find the correlation between two variables and discuss your results.
Time to determine the temperature change along a wallcountermeasurements were taken. Using the least squares method,Describe the temperature change as a function of time with the data.t (min) 0 1 2 3 4 5 6T (o C) 20 23 33 34 56 79 98
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blease use hand calculaton dont use any doftware
The scatter plot below shows data for the average cost of a high-end computer (y, in dollars) in the year x years since 2000. The least squares regression line is given by yˆ=−1677+314x. A coordinate plane has a horizontal x-axis labeled Year from 4 to 12 in increments of 2 and a vertical y-axis labeled Cost in dollars from 0 to 2000 in increments of 500. The following points are plotted: left-parenthesis 6 comma 250 right-parenthesis, left-parenthesis 7 comma 550 right-parenthesis, left-parenthesis 9 comma 1000 right-parenthesis, left-parenthesis 10 comma 1300 right-parenthesis, and left-parenthesis 11 comma 2000 right-parenthesis. A line rises from left to right, passing through left-parenthesis 7 comma 550 right-parenthesis and left-parenthesis 10 comma 1500 right-parenthesis. All coordinate are approximate. Interpret the slope of the least squares regression line. Select the correct answer below: On average, the average cost of a high-end computer is…
Help me answer all parts except A&D
We want to write the least-squares equation ý a+ bx, using the given printout. Predictor Coef SE Coef Constant 316.27 28.31 11.24 0.002 Elevation -32.660 3.511 -8.79 0.003 S 11.0603 R-iq 95.1N Recall that a is the intercept and b is the slope of the line. Since the elevation is the explanatory variable, x, the coefficient of the x-term is the slope of the line. From the printout, this corresponds to the table value in the "Elevation" row, and "Coef" column. Therefore, The intercept is given by the value of the constant term. There is no variable, but the Minitab printout classifies this value as a "coefficient." (Note: This may or may not coincide with your previous experience with the terms "constant" and "coefficient," but it is mathematically correct for reasons that we will not explore in this tutorial.) The value in the "Constant" row and "Coef" column is 316.27, Therefore, a Substitute these values into the least-square equation. 9 -a+ bx
You may need to use the appropriate technology to answer this question. Suppose data on advertising expenditures and revenue (both in thousands of dollars) for a certain restaurant follow. Advertising Expenditures Revenue 19 2 33 4 43 39 10 53 14 53 20 54 (a) Let x equal advertising expenditures (in thousands of dollars) and y equal revenue (in thousands of dollars). Use the method of least squares to develop a stralght line approximation of the relationship between the two variables. (Round your numerical values to two decimal places.)
The data for temperature (x) and number of ice cream cones sold per hour (y) is shown. x 65 70 75 80 85 90 95 100 105 y 8 10 11 13 12 16 19 22 23 It would be reasonable to use the least squares regression line to predict the number of ice cream cones sold when it is 50 degrees. True False

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