A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the companyrandomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company willconduct a simple linear regression on the data below:River FallsHudsonEllsworthPrescottRock ElmStillwaterSelect one:a. 78.39%b. 88.54%O c. 161.39%O d. 100%CityWhat percentage of the total variation in the candy bar sales is explained by prices?e. 48.19%Price ($)1.301.601.802.002.402.90Sales1009090403832

Correlation is the measure of association between the two numerical variable. Correlation is denoted…

Answered: A candy bar manufacturer is interested…

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 below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. X Y 11.4 8.6 7.2 3.6 13.5 11.3 10.1 x = thousands of automatic weapons y = murders per 100,000 residents 2.4 2.8 2.3 0.9 7 6.1 6.6 5.9 4.7 This data can be modeled by the equation y = 0.83x +4.06. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. Answer = A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 11 thousand automatic weapons? Round to 3 decimal places.
How do you figure this out using conjoint analysis in a linear regression? Determine how various attributes impact the purchase of a car. There are four attributes, each with three levels: Brand: Ford = 1, Chrysler = 2, GM = 3 MPG: 15 MPG = 1, 20 MPG = 2, 25 MPG = 3 Horsepower (HP): 100 HP = 1, 150 HP = 2, 200 HP = 3 Price: $18,000 = 1, $21,000 = 2, $24,000 = 3 The nine product profiles ranked in the data file were evaluated by a consumer. (a) For this market segment, rank the product attributes from most important to least important. Below is the data provided. Brand MPG Power Price Rank 1 1 1 1 4 1 2 2 3 7 1 3 3 2 3 2 1 2 2 6 2 2 3 1 2 2 3 1 3 9 3 1 3 3 8 3 2 1 2 5 3 3 2 1 1
Roller coasters get their speed as a result of dropping down a steep incline. The table below gives height of a drop and the speed achieved for different roller coasters around the world. Drop in Meters (m 25 30 28 58 55 40 90 100 Speed of the coaster (k.p.h) 80 90 78 93 90 93 105 128 Have your calculator find the linear regression for the roller coaster data above. Write the linear model, clearly define the variables and state correlation coefficient and clearly interpret the slope. Use the model to find the drop height that will result in a coaster speed of 150 kph. Have your calculator find the exponential regression for this data. Write the exponential model, clearly define the variables and state correlation coefficient. Use the model to find the drop height that will result in a…
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Select the most appropriate response. If the correlation between a person’s age and annual income is 0.60, then the coefficient of determination tells us that: 36% of the variation in a person’s annual income can be explained by the predictor variable age. 36% of a person’s annual income can be explained by their age 60% of the variation in a person’s annual income can be explained by the predictor variable age 60% of a person’s annual income can be explained by their age
Is there a relationship between the weight and price of a mountain bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the bike's price. Weight (LB) 32 33 29 29 34 37 28 30 34 30 Price ($) 980 350 430 710 930 160 590 530 180 1090 a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the y-intercept have contextual meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the bike? a. Which scatterplot below correctly shows the data? A. 254001200xy A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…
In multiple regression, when all independent variables are considered but the order in which they are added to the model is determined by the amount it contributes to the dependent variable, it is called: a.Two step b.Stepwise c.Simultaneous d.Backward step
One of the biggest changes in higher education in recent years has been the growth of online universities. The Online Education Database is an independent organization whose mission is to build a comprehensive list of the top accredited online colleges. The following table shows the retention rate (%) and the graduation rate (%) for 29 online colleges.a). Use Excel Data Analysis Tool – Regression to get the relationship between the two variables;b). Create a scatter diagram for the two variables and display regression equation and R square on chart, then explain the relationship between the variables;c). Did the estimated regression equation provide a good fit?d). Suppose you were the president of South University. After reviewing the results, would you be able to use the regression result for forecasting. College RR(%) GR(%) Western International University 7 25 South University 51 25 University of Phoenix 4 28 American InterContinental University 29 32 Franklin…
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Susan, a personal trainer, was interested in whether or not there was a linear relationship between the number of visits her clients made to the gym each week and the average amount of time her clients exercised per visit. She took the following data. Client 1 2 3 4 5 6 Number of visits per week 1 3 4 2 3 5 Average time spent exercising per visit (hours) 2 1.5 1 2 2 0.30 Using the best fit line, estimate the average time spent exercising per visit for 4 visits per week. Group of answer choices 1.03 hours 1 hour 10.3 hours 2 hours

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