Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand fortheir line of company speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are themain drivers in sales and wants to use regression analysis to figure out which factor drives more demand for its particular market.Pertinent information was collected by an extensive marketing project that lasted over the past 12 years and was reduced to the datathat follow:YEAR1234567B9101112UNIT SALES(THOUSANDS)398698898y bar1,3041,1631,1958981,2009821,235875811PRICE $ PERUNIT283209213220209200220209230213216243ADVERTISING($000)6218211,2001,4051,2101,3048751,200691875691691a. Perform a regression analysis based on these data using Excel.Note: Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.Priceadvertising

Here dependent variable (y) is Unit sales.There are two independent variables.Price per unit (x1)…

Answered: a. Perform a regression analysis based…

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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Use StatKey or other technology to find the regression line to predict Y from X using the following data. Click here to access StatKey. Round your answers to three decimal places. The regression equation is Y = X 6 Y 3.5 10 8 + 4 2 14 12 12 8.5 X.
The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $7 million. Is the result close to the actual number of viewers, 5.2 million? Use a significance level of 0.05. Salary (millions of $) 108 14 5 8 5.1 4.3 7.8 2.5 Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to three decimal places as needed.) X 1 1 5 8 5.7 8.2 10.9 4.4
How many independent variables are involved in a multiple regression equation? a. One b. Zero c. Two or more d. At least three
Use the data below for the PHONES questions that follow. Data compiled from the CIA World Factbook, https://www.cia.gov/. The number of cell phones in use in a country can be approximated from the number of main lines in use in that country by using the regression equation yhat=25+3x which had an R² of about 90%. (The numbers here are millions. For example, "1.2" would represent 1.2 million or 1,200,000.) PHONES 1 At the time the data was collected, the USA had about 314 million cell phones in use and about 150 million main lines in use. What was the residual for the USA? Enter a number of millions. For example, if your answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.
We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed. wage = -3.07 + 1.52 educ Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1
Use the Women's Earnings scatterplot below to answer the questions. Women's Earnings as a Percentage of Men's Earnings 90 80 70 60 50 y = 0.617x - 1156.3 40 R² = 0.9302 à 30 20 10 1979 1984 1989 1994 1999 2004 2009 Year What is the independent variable and what does it represent? Year Percentage Income in dollars CO2 Percentage
Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 1.5.
For the data in the table, find the regression equation. Here, x gives the number of years of experience for nurses, and y is their annual salary (in $1000's). Round the slope and y-intercept to two decimals, then use your equation to answer the questions below. Years of Salary Experience ($1000's) 40 4 42 43 45 10 46 13 52 15 53 17 56 21 58 22 60 a. What is the expected salary (in $1000's) for a nurse with no work experience? b. By what amount (in $1000's) does an extra year of experience boost the annual salary?
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
For the given data below, Solve, a. Find the regression equation, y = b0 + b1x.b. If x = 170 orders, how many shipments are expected?
Find the intercept (b0) for the regression equation for the following values. Round to 3 decimal places. Intercept xi yi 33 180 25 170 50 200 65 172 57 160 27 165

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a. Perform a regression analysis based on these data using Excel. Note: Negative values should be indicated by a minus sign. Round your answers to 4 decimal places. y bar Price advertising