HatsforAll, a major producer of hats, hired a research firm to study the demand for its hats. The research firm used 20 years of data on sales of the company's hatsand included two independent variables: the annual average price of the hats and the annual average winter temperature in the company's marketing areas. (Thetheory behind the temperature variable is that consumers are more likely to buy hats when the temperature is colder.) The estimated coefficient for the price variableis -5.8 with a standard error of 0.8, and the estimated coefficient for the temperature variable is -20.8 with a standard error of 15.6. Based on the results of surveycards included with the hats, the research firm is confident that higher-income people buy more hats.In addition to the above two independent variables, the researcher should also includeestimate more accurate.The coefficient of the temperature variable suggests that it issignificantis a third explanatory variable to make the

b1=-5.8, SEb1=0.8b2=-20.8, SEb2=15.6

Answered: HatsforAll, a major producer of hats,…

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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Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day. a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?
The condition of an independent variable being correlated to one or more other independent variables is referred to as nonlinearity. statistical significance. multicollinearity. linearity.
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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
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Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
What is the coefficient of the dummy variable? What is the meaning of the coefficient of the dummy variable?

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