Required informationExercise 5A-5 (Algo) Least-Squares Regression [LO5-11]George Caloz & Frères, located in Grenchen, Switzerland, makes luxury custom watches in small lots. One of thecompany's products, a platinum diving watch, goes through an etching process. The company has recorded etching costsas follows over the last six weeks:Mook123Y-Units10126B11Req 2ATotal EtchingCast$ 2720312024For planning purposes, management would like to know the variable etching cost per unit and the total fixed etching costper week.Exercise 5A-5 Part 2 (Algo)2-a. Using the least-squares regression method, estimate the variable etching cost per unit and the total fixed etching cost per week.2-b. Express these estimates in the form Y= a + bX30$ 152Complete this question by entering your answers in the tabs below.Req 20Express these estimates in the form Y = a + bx. (Round your answers to 2 decimal places.)< Req ZAReq 28 >

The given paired observations for "Units" and "Total Etching Cost In $)" are:WeekUnitsTotal Etching…

Answered: Required information Exercise 5A-5…

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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An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. LOADING... Click here to view the weight and gas mileage data. Question content area bottom Part 1 (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. ModifyingAbove y with caretyequals=enter your response herexplus+(enter your response here) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
In baseball, two statistics, the ERA (Earned Run Average) and the WHIP (Walks and Hits per Inning Pitched), are used to measure the quality of pitchers. For both measures, smaller values indicate higher quality. The following computer output gives the results from predicting ERA by using WHIP in a least-squares regression for the 2017 baseball season. Variable DF Estimate SE T Intercept 1 -5.0 0.26 - 19.3 WHIP 1 6.8 0.14 47.4 Which of the following statements is the best interpretation of the value 6.8 shown in the output? ERA is predicted to increase by 6.8 units for each 1 unit increase of WHIP. WHIP is predicted to increase by 6.8 units for each 1 unit increase of ERA. For a pitcher with 0 units of WHIP, the ERA is predicted to be approximately 6.8 units. For a pitcher with 0 units of ERA, the WHIP is predicted to be approximately 6.8 units. Approximately 6.8% of the variability in ERA is due to its linear relationship with WHIP.
A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. Click the icon to view the children's data. Data table (a) Find the least-squares regression line treating height y =x+ (O (Round the slope to three decimal places and round the d Height (inches), x Head Circumference (inches), y O. 28 17.6 24.5 17.1 25.75 17.1 25.75 17.5 24.25 17.0 27.75 17.7 26.5 17.3 27.25 17.6 26.5 17.3 26.5 17.5 27.75 17.6 Print Done Help me solve this View an example Get more help - Media - Clear all Check answer
Canvas -→ X C0| ® E Exhibit 6 Part of an Excel regression output relating salary for programmer (dependent variable) with three independent variables: Test score, Graduate Degree, and Experience is shown below. Coeffic. Std. Err. t Stat P-value Intercept 7.9448 7.3808 1.0764 0.2977 Test Score 1.1476 0.2976 4.8561 0.0850 Grad. 0.1969 0.0899 2.1905 0.0011 Degree Experience -2.2804 1.9866 -1.0479 0.3679 Refer to Exhibit 6. Based on the Excel output, at 95% confidence (alpha = 0.05) which of the independent variables in the output contributes significantly to explain salary? O Experience Grad Degree Intercept Test score
Name Her Age His Age Barack and Michelle Obama 45 47 George W. and Laura Bush 54 54 Bill and Hillary Clinton 45 46 Ronald and Nancy Reagan 55 64 Gerald and Betty Ford 59 69 Lyndon and Lady Bird Johnson 56 61 John and Jacqueline Kennedy 31 43 Dwight and Mamie Eisenhower 50 55 (c) Remove the outlier and compute the least-squares regression line for predicting the president's age from first lady's age. Round the slope and y -intercept values to at least four decimal places. Regression line equation: =y
Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x %3D where x is metatarsal-to-femur ratio and ŷ is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct an 80% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. Lower limit: Upper limit:
A researcher conducts a multiple regression with Y as the dependent variable and X1, X2, X3 and X4 as explanatory variables. Using the regression output below, fully describe this model and discuss important parts of the output. What is the predicted value of Y if X1 = 3, X2 = 15, X3 = 7 and X4 = 0.003? %3D SUMMARY OUTPUT Regression Staistics Muliple R R Square Adjusted R Square Standard Emor Observations 0.7236 0.5236 0.5159 5.3928 252 ANOVA Significance F 1. 10662E-38 SS MS Regression Residual 1973 9392 29.0820 67.8749 7895.7567 7183.2599 4 247 Total 251 15079.0166 Upper 95% 33.4049 Coefficients Standard Eror t Stat Pvalue 2.2273 0.026830873 Lower 95% 7.9594 2.0508 Intercept X1 17.7278 1.5583 0.2750 5.6662 4.05265E-08 1.0166 2.0999 X2 1.8376 0.1997 9.1999 1.4442 -74708 -3721 4324 1.55861E-17 2.2310 X3 55100 -5.5348 7.94036E-08 -3.5492 X4 -3.1079 1887 8435 -0.0016 0.998687788 3715 2166
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