You are giving the regression equation of how the sales trend varies with time:y= 300 + 25xWhere:x=quarter (x increases by two for each new quarter)y=units salesInstructions:Forecast the sales for each quarter using the following SVs:Q2Q3Q4Q1-5%+13%9%+11%

Answered: Image /qna-images/answer/261a766a-b24c-4e5b-a201-39c32e067e75.jpg

Answered: You are giving the regression equation…

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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While collecting data on shoe sizes (y) compared to heights in inches (x) of male students in the class a student found that the shoe sizes ranged from size 7 to size 11 and the heights of the students ranged from 60 to 72 inches. The student ran a linear regression to get the function = 1 -x- 3 13 where y is the shoe size and is the height of the person in inches. What would be the shoe size for a student who was 73 inches tall? Shoe sizes only show up in incriments of 0.5 (ie. 7, 7.5, 8, 8.5, 9, 9.5, ....) so round to the nearest 1/2 shoe size. Show all your work.
Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.
A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best graphic to use to evaluate the appropriateness of the model?
Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
Smith is studying the relationship between length (X) and weight (Y) of infants. Please help him fit an exponential growth model to find the relationship between length and weight. Write down the model and explain how to fit the model (i.e., how to estimate regression coefficients) and what the intercept is for the relationship between X and Y (in symbolic form).
Recently there has been a rise in fatal accidents caused by “distracted driving.” The United States National Highway Traffic Safety Administration (NHSTA) defines a distraction as anything that diverts attention from driving. The following model estimates the trend in distracted driving accidents over time based on data from the NHSTA:D = 0.015t - 29.97 In this model, D is the decimal to be turned into a percentage of all fatal accidents caused by distracted driving, and t is any calendar year between 2000 and 2020. Use the model to estimate the rate for 2005 and 2020. Note: this means to plug n 2005 for t and simplify and then turn your answer into a percent. Then plug in 2020 for t and simplify and then turn your answer into a percent.
In simple linear regression, the coefficient of determination measures: a.The amount of variability of the y variable that is explained by the x variable b.The amount of variability of the x variable that is explained by the y variable c.The amount of variability between the treatments d.The amount of variability within the treatments
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.7 per 10 million people? X Click the icon to view the data. Find the equation of the regression line. ŷ=+x (Round the constant to one decimal place as needed. Round the coefficient to thre Data table Internet Users Per 100 80.1 79.2 78.4 45 82.9 38.4 89.5 88.8 79.1 83.3 52.7 76.5 57.1 79.4 93.1 94.8 64.5 57.7 67.3 94.1 84.6 86.6 78.5 Nobel Laureates 5.5 24.4 8.7 0.1 6.1 0.1 25.4 7.6 9 12.8 1.9 12.6 3.3 1.5 11.3 25.5 3.1 1.9 1.7 32 31.3 18.8 10.8
Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20minutes. How does the result compare to the actual tip amount of $4.55? Distance 1.40 1.65 0.68 1.32 8.51 1.80 1.02 12.71 Time 18.00 11.00 6.00 8.00 31.00 25.00 8.00 27.00 Fare 12.30 9.80 6.30 7.80 31.75 16.30 7.80 36.80 Tip 2.46 1.96 1.89 0.00 2.98 1.50 2.34 0.00 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.) The best predicted tip for a ride that takes 20 minutes is $enter your response here. (Round to the…
For 39 nations, a correlation of 0.887 was found between y = Internet use (%) and x = gross domestic product (GDP, in thousands of dollars per capita). The regression equation is y = -3.68 + 1.73x. Complete parts (a) through (c). a. Based on the correlation value, the slope had to be positive. Why? A. The slope and correlation are positive because gross domestic product could not be negative. B. The correlation and the slope are positive because the y-intercept is negative. C. That is a very unusual fact, because the slope and correlation usually have different signs. D. Although slope and correlation usually have different values, they always have the same sign.

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You are giving the regression equation of how the sales trend varies with time: y= 300 + 25x Where: x=quarter (x increases by two for each new quarter) y=units sales Instructions: Forecast the sales for each quarter using the following SVs: Q2 Q3 Q4 Q1 -5% +13% 9% +11%