wwwSTATISTICS - XII14. The following data relateto advertising exnenditure and sales of 10 major shopsin a city.ugeAdvertising expenditure (lakhs)Salės (lakhs)Mean1015SD53.Coefficient ofcorrelation= 0.65a) Calculate sales when advertising expenditure is 13 lakhs.b) Calculate advertising expenditufé when sales is 20 lakhs.15. The following calculations have been made for the price of 12 stocks (X) on BSEon a certain day along with volume of sales on shares (Y). From these calculationscalculate the regression equation of price of stocks on volume of shares.Ex- 580, Ey = 370, E xy = 11494, . x = 41658, Ey= 1720616. While studying about the relationship between scores on statistics (X) and scoreson accountancy (Y) the following regression equations were obtained.Regression equation of Y on x: 3y – 2x-100=0Regression equation of X on Y: 4y -3x+ 50 0a) Find the correlation coefficientb) Estimate the scores on Statistics if a student got 50 score in Accountancy.Find the mean values of the variables X and Y for the following regression equations.Regression line of Y on X: 2y-x= 50Regression line of X on Y: 3y- 2x= 1018. The following regression equations are obtained when studying about the demand(X) and supply(Y) of a group of commodities.26-3x-2y 031-6x-y 0a) Identify regression lines and find the correlation coefficient.b) Find the mean values of the variables X and Y. 54 21422of a particular commodity.15253020153020valuate sales when the price of theent for exercising daily in minutes(-15gern whe eaied

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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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Select all the charts that violate the conditions for linear regression. These are residual plots so the red line represents the average residual, zero. 미 Od (a) (d) 매 Get help: Video (b) (e) (c) (1)
A set of X and Y scores has SSX = 5, SSY = 7.5, and SP = 15. The regression equation for these scores will have a slope constant of 2. true or false?
A biologist wants to predict the height of male giraffes, y, in feet, given their age, x1, in years, weight, x2, in pounds, and neck length, x3, in feet. She obtains the multiple regression equation yˆ=7.36+0.00895x1+0.000426x2+0.913x3. Predict the height of a 12-year-old giraffe that weighs 3,100 pounds and has a 7-foot-long neck, rounding to the nearest foot.
Suppose that for a typical FedEx package delivery, the cost of the shipment is a function of the weight of the package measured in ounces. You want to try to predict the cost of a typical shipment given package dimensions. If 10 packages in a city are sampled and the regression output is given below, report the regression equation. 1) (cost of delivery) = 1.468*(weight) - 23.015 2) (weight) = -23.015*(cost of delivery) + 1.468 3) (cost of delivery) = -23.015*(weight) + 1.468 4) (cost of delivery) = 1.468*(weight) 5) (weight) = 1.468*(cost of delivery) - 23.015
Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.010.01 level of significance. Average Temperatures and Snow Accumulations Average Temperature (℉℉) 38 30 17 39 45 22 34 24 29 38 Snow Accumulation (in.in.) 6 19 27 5 13 26 26 14 13 5 Copy Data
Tom has been gathering data concerning the cost of a spa treatment, y', during the before Valentine's Day. The only independent variable that he has considered is the number of minutes, "x," in the treatment. Suppose Tom collects data on the relationship between the number of minutes in a treatment and the resulting cost of we the treatment. Tom finds that the correlation between cost and number of minutes is strong and positive. Therefore, he has performed a linear regression analysis on his data. His results are that the constant "a" is 35, and the coefficient "b1" for the independent variable is 1.3. Which of the following is the correct linear regression equation that would allow Tom to predict the cost of a spa treatment given the number of minutes? Oy = 78x + 35 Oy' = 1.3x + 35 %3D Oy = 78x - 1.3 %3D OY = -1.3x - 35
The average August temperatures (y) and geographic latitudes (x) of 13 cities in the United States were studied. The regression equation for these data isTemperature = 127 -1.68*(latitude)What is the slope of the line? Estimate the mean August temperature for a city with latitude of 11.Use 2 decimal placesSan Francisco has a latitude of 40. What would you predict for the mean August temperature of San Francisco?Use 2 decimal placesGiven that the mean August temperature in San Francisco is actually 70 calculate the residual (prediction error) for San Francisco.It should be observed minus predicted. If you do it wrong your answer have the positive and negative switchedUse 2 decimal placesThe latitude at the equator is 0. Estimate the average August temperature at the equator.Use 1 decimal place
Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ y^ is the predicted final exam score. ?̂= 1.48+75.64 The scatter plot displays her results. What is the predicted ?̂ y^‑value when a student spends 13 hours studying? Round your answer to one decimal place. y^= ? Select the correct interpretation. The above predicted value of ?̂ y^ is _____ a. the predicted score of 13 out of 15 students. b. the predicted final math test score if a student studies 13 hours during the year. c. the math final test score that 13 students beat. d. what any student will score on the final exam if they study at least 13 hours.
Ariel was running analyses over and over in census data and came across a correlation between weight and debt (r=.78). Independent variable is weight and dependent variable is debt. b) Curious Ariel noted some statistics on these weight (M=160lb, SD=15lb) and debt (M=196k, SD=20k). If Ariel wanted to calculate a regression equation, what would her slope and intercept be?
An investigation into the relationship between an adolescent mother's age x in years and the birth weight y of her baby in grams yielded the regression equation y= - 1163.45 + 245.15x as well as r = .88369, r2= .78091, SSE = 337212.45, and s= 205.30844 1) What is the predicted birth weight for a baby brn to a 17 year old woman? 2) What is the propotion of the variability in the weights of babies born to adolescent mothers that is accounted for by the mother's age? 3) For every additional year in the mother's age that mean birth weight of the baby? (a) increases by about 245g (b) decreases by about 245g (c) increases by about 1163g (d) increases by about 1163g (e) changes by an amount that cannot be determined from the information given.
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construct and interpret a 98% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y=-1.106x+15,759.462 Oil_produced,_x Oil_imported,_y5,816 9,3455,741 9,1245,660 9,6325,405 10,0095,155 10,1685,059 10,1055,015 10,055

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15. The following calculations have been made for the price of 12 stocks (X) on BSE on a certain day along with volume of sales on shares (Y), From these calculations calculate the regression equation of price of stocks on volume of shares. Ex- 580, E y 370, E xy- 11494, Ex-41658, Ey 17206