What is the mean frisbee radius with 95% confidence interval?Hint: (95% CI:1.96*SE) where is the population mean and can be approximated by pr2.2 Estimate disc throw length using multiple linear regressionYou have collected data to estimate disc throw length of a frisbee. You decided to construct a multiple linearregression model, and your input features are (i) radius of frisbee in cm, (II) weight of frisbee in kg, (III) designof frisbee, and (lv) material of frisbee. Your company has three different designs and two different materials.You use one-hot encoding to convert categorical variables (design and material) to numerical variables. If youhave 200 data points in your dataset, what is the shape of your design matrix X? Note that there is no bias.X.shape=Pa

Given that the dataset contains 200 data points, we need to determine the shape of the design…

Answered: 2.2 Estimate disc throw length using…

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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The table shows a part of an output of a linear regression model predicting the average fare on different flight routes. Data Table Regression Table Coefficient Constant 95.80976147 COUPON −9.61654124 DISTANCE 0.080733811 PAX −0.000167343 What is the difference in prediction of the following two routes? Route A that is 3,000 miles, with COUPON=1.5 and PAX=6,000 Route B that is 3,000 miles, with COUPON=1.2 and PAX=6,000.
estion 7 of 15 Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is y = -114.05 +2.17x. On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ŷ, when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bags Using the predicted value you just found, compute the residual at this temperature. residual = ice bags DOLL
a)Find the equation of the least-squares regression line for the data. (Where x is the independent variable.) Round constants to the nearest hundredth. b)Use the equation from part (a) to determine, to the nearest centimeter, the projected wingspan of a pterosaur if its humerus is 53 centimeters.
Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year. Year Number of Patients Robbery Rate per 1,000 Population The simple linear regression equation that shows the best relationship between the number of patients and the robbery rate is (round your responses to three decimal places) where y Number of Patients and x = Robbery Rate. = 1 2 3 4 6 7 36 33 40 41 55 60 58.3 61.1 73.4 75.7 81.1 89.0 101.1 5 40 8 54 94.8 9 58 103.3 10 61 116.2
Cereals For many people, breakfast cereal is an im-portant source of fiber in their diets. Cereals also con-tain potassium, a mineral shown to be associated with maintaining a healthy blood pressure. An analysis of theamount of fiber (in grams) and the potassium content (inmilligrams) in servings of 77 breakfast cereals producedthe regression model Potassium = 38 + 27 Fiber. Ifyour cereal provides 9 grams of fiber per serving, howmuch potassium does the model estimate you will get?
KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
Mike's Stables has two different possible cost drivers (trainer hours and number of horses) for budgeting the cost of horses training. The most recent results of the two regression analysis are as follows: Trainer's hours: SUMMARY OUTPUT – Regression Results Regression Statistics R Square 0.56 Coefficients t Stat Intercept 1,004.65 4.61 X Variable 1 $22.99 7.11 Number of horses: SUMMARY OUTPUT – Regression Results Regression Statistics R Square 0.63 Coefficients t Stat Intercept $5,240.95 4.44 X Variable 1 $951.48 3.50 What is the estimated total training horses cost for the coming year if 15,000 trainer hours are incurred and the stable has 350 horses to be trained, based upon the best cost driver?
Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.493x - 83.403. Complete parts (a) and (b) below. A Average Weekly Wages (state), x Average Weekly Wages (federal), y 764 1003 766 1048 791 1119 (a) Find the coefficient of determination and interpret the result. r² = 0 (Round to three decimal places as needed.) 800 1152 843 1201 887 1250 924 1277 939 1306
Used cars 2010 Vehix.com offered several used ToyotaCorollas for sale. The following table displays the ages ofthe cars and the advertised prices. a) Make a scatterplot for these data.b) Do you think a linear model is appropriate? Explain.c) Find the equation of the regression line. d) Check the residuals to see if the conditions for infer-ence are met. Age (yr) Price ($) Age (yr) Price ($)1 15988 6 99951 13988 6 119882 14488 7 89903 10995 8 94883 13998 8 89954 13622 9 59904 12810 10 41005 9988 12 2995
The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= - 0.972. The least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is y= - 0.0070x + 44.4405. Complete parts (a) and (b) below. Click the icon to view the data table. ..... (a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %. (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variance in is by the linear model. Data Table (Round to one decimal p Full data set gas mileage Miles per Weight (pounds), x Weight (pounds), x Miles per Gallon, y Car Car Gallon, y…
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?

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