Suppose multiple linear regression model is fitted with seven independent variable and revealed the following results.Variables Entered/RemovedaMethodEnterModelVariables EnteredVariables RemovedX7, X2, X4, X1, х6, хз, х5ba. Dependent Variable: Yb. All requested variables enteredModel SummaryStd. Error of theAdjusted RSquare.500ModelRR SquareEstimate10.99021754a568a. Predictors: (Constant), X7, X2, X4, X1, X6, X3, X5ANOVAaModelSum of Squares6998.009DfMean Square999.716FSig.1Regression8.277.000b7Residual5314.50344120.784Total12312.51251a. Dependent Variable: Yb. Predictors: (Constant), X7, X2, X4, X1, X8, X3, X5CoefficientsaUnstandardizedStandardizedCollinearity StatisticsVIFCoefficientsCoefficients2 www.youtube.com · 10mModelBStd. ErrorBetatSig.Tolerance1 (Constant)60.5549.4956.377.000PSL Transfer News | Kaizer Chiefs NewX1.001.001.1641.472.148.7881.269Recommended: Madi Media FootballX2.087.0482001.809.077.8011.249000000n401.000P Type here to search VIT1 (Constant)60.5549.4956.377.000X1.001.001.1641.472.148.7881.269X2.087.0482001.809.077.8011.249X3.009.009.133.948.349.5001.999X4-.043.017-.290-2.466.018.7101.408X5.047.012.5593.905.000.4782.090X6209.130.1881.607.115.7191.391X7005.006.1168753875551.800a. Dependent Variable: Ya) Is it necessary to use the t-test to test for the significance of each coefficient? Justify your answer.b) What can you say about the correlation coefficient value in the summary model table?Question (c) and (d) are based on backward elimination method application:c) Which variable would be removed first? Justify your answer.d) After your findings in part (c), is it possible to remove another variable from the same results? Justify your answer.e)i) In the output, what does the statistics 'VIF' and Tolerance' assess?ii) How do they differ from each other?iii) Explain whether you are concerned about these values?f) If a simple regression analysis is performed with X3 as the only independent variable, the Sum of Squares Error (SSE) e www.above multiple regression model with seven independent variables. Test if this simple regression model is signifi PSL TransRecommeFor the toolbar. press ALT+F10 (PC) or ALT+FN+F10 (Mac).BI U S Paragraphv ArialQ 6 2 = = = = E E x' X 814px

Variables Entered/Removeda Model Variables Entered Variables Removed Method Enter 1 X7, X2, X4, X1, X6, X3, X5b a. Dependent Variable: Y b. All requested variables entered Model Summary R Square .568 Adjusted R Square .500 Std. Error of the Estimate 10.9902 Model R .754a a. Predictors: (Constant), X7, X2, X4, X1, X6, X3, X5 ANOVA Sum of Squares 6998.009 Mean Square 999.716 Model Df F Sig. 000b 1 Regression 8.277 Residual 5314.503 44 120.784 Total 12312.512 51 a. Dependent Variable: Y b. Predictors: (Constant), X7, X2, X4, X1, X6, X3, X5 Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics VIF O www.youtube.com · 10m Std. Error 9.495 Model B 60.554 Beta Sig. .000 Tolerance 1 (Constant) 6.377 PSL Transfer News | Kaizer Chiefs X1 .001 .001 .164 1.472 .148 .788 1.269 Recommended: Madi Media Foof X2 .087 .048 200 1.809 .077 .801 1.249 000 040 Enn 4000

Variables Entered/Removeda Model Variables Entered Variables Removed Method Enter 1 X7, X2, X4, X1, X6, X3, X5b a. Dependent Variable: Y b. All requested variables entered Model Summary R Square .568 Adjusted R Square .500 Std. Error of the Estimate 10.9902 Model R .754a a. Predictors: (Constant), X7, X2, X4, X1, X6, X3, X5 ANOVA Sum of Squares 6998.009 Mean Square 999.716 Model Df F Sig. 000b 1 Regression 8.277 Residual 5314.503 44 120.784 Total 12312.512 51 a. Dependent Variable: Y b. Predictors: (Constant), X7, X2, X4, X1, X6, X3, X5 Coefficients Unstandardized Coefficients Standardized Coefficients Collinearity Statistics VIF O www.youtube.com · 10m Std. Error 9.495 Model B 60.554 Beta Sig. .000 Tolerance 1 (Constant) 6.377 PSL Transfer News | Kaizer Chiefs X1 .001 .001 .164 1.472 .148 .788 1.269 Recommended: Madi Media Foof X2 .087 .048 200 1.809 .077 .801 1.249 000 040 Enn 4000

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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Step 4 The following table summarizes the given data and the forecast values. There will not be a forecast error for the first month. Complete the columns for the forecast error and squared forecast error. Month Value Forecast Value 1 2 3 4 5 6 7 19 27 23 28 24 23 28 19 23 23 24.25 24.2 24 Forecast Error Actual - Forecast Submit Skip (you cannot come back) 27 19 = 8 0 5 -0.25 4 Total Squared Forecast Error (Actual - Forecast)² (8)² = 64 0 1.44 The MSE will be the average of the squared forecast error column. Find the average of this column, rounding the result to two decimal places. MSE =
Suppose you have access to a database with the variables listed below. Choose two variables you are interested in exploring that may be related (a predictor and outcome). Which variable is your y (outcome) and which is your x (predictor)? *Hint: which one may predict the other? Example: hot weather may predict sunburns.
Christine is a sales manager for a car rental company. She has a scatterplot with data regarding the years of experience of sales representatives and percent of satisfied customers. What information would the scatterplot below indicate? Select all that apply. 100 90 80 70 50 40 30 20 10 1 3 5 6 7 Years of Experience of Salesperson O Satisfaction rate is the independent variable. O Satisfaction rate is the dependent variable. O Years of experience is the independent variable. O Years of experience is the dependent variable. O Christine should consider customer satisfaction training for her more novice representatives. O There is a positive correlation between years of experience and customer satisfaction. O There is a negative correlation between years of experience and customer satisfaction. O There is no correlation between years of experience and customer satisfaction. Percent of Satisfied Customers
Please do not give solution in image format thanku The distribution of hemoglobin in grams per deciliter of blood is approximately N(15,2) in women and approximately N(16,3) in men. a. What percent of men have less hemoglobin than the women’s mean hemoglobin? b. What percent of men have more hemoglobin than the women’s mean hemoglobin? c. What percent of women have more hemoglobin than the men’s mean hemoglobin?
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An engineer wants to determine how the weight of a gas powered car, x, affects gas mileage, y. The accompanying days represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. weight Miles per (pounds), x Gallon, y 3797 16 3897 16 2704 24 3608 20 3360 22 3040 22 3787 17 2618 24 3509 18 3798 16 3399 17 interpret the slope y-intercept, if appropriate. Choose the correct answer below for y hat = -0.00661x + 41.80 a) A weightless car will get ____ miles per gallon, on average. It is not appropriate to interpret the slope. b) for every pound added to the weight of the car, mileage in the city will…
The data represent the heights in feet and the number of stories of the tallest buildings in a city. Height, x 793 388 825 404 439 550 931 669 532 Stories, y 57 26 58 31 33 36 60 49 34 Scatter Plot for the Heights (in Feet) and Number of Stories of the Buildings. 90- 50- 40- 30- 20- 10- 100 1200 400 300 700 Part: 0 /3 Part 1 of 3 Find the value for r. Round your answer to at least three decimal places.
A+ F3 # F a. What are the relative and absolute changes in the Charlie Card bus fare? You don't have to do this in your head, without a calculator, but you should be able to. b. Create a spreadsheet for these data, with eight rows (one for each of the eight categories) and three columns, for the category name, the existing fare and the proposed fare. Create a properly labeled bar graph to display the data. c. Label the next two columns appropriately to hold the relative and absolute changes. Fill those columns with Excel formulas to compute the correct values. Do not compute the values elsewhere and enter them in the spreadsheet as numbers. [See the back of the book for a hint.] F4 4 d. Imagine that you are addressing a public meeting about these fare increases. How would you argue that an unfair burden is being placed on people who pay using a Charlie Ticket? How would you argue that senior citizens are most hard hit? 2 (6 14 13) 3 nts - The table below shows the salarestructure of…
please label each part
K Disk drives have been getting larger. Their capacity is now often given in terabytes (TB) where 1 TB = 1000 gigabytes, or about a trillion bytes. A survey of prices for external disk drives found the data shown to the right. For this data, we want to predict Price from Capacity. Complete parts a through i below. Click the icon to view the disk drive data and summary statistics. Disk Drive Data and Summary Statistics Capacity (in TB) 0.5 1.0 2.0 3.0 4.0 6.0 8.0 12.0 32.0 x = 7.611 SD(x) = 9.85 r = 0.987 --- Print Price (in $) 58.79 75.79 114.00 105.95 146.45 425.49 594.00 1074.00 4464.49 y = 784.329 SD(y) = 1420.27 Done X A. It indicates the price for a hard drive with no capacity. It is meaningless and should not be interpreted. B. It indicates the additional capacity in TB for each additional dollar of price. It is meaningful in that it could be interpreted as the cost of the parts common to all drives.
Please give maximum value for this data!