Suppose that we performed an estimate of the determinants of players' salaries forthe 2018 NFL season. The R? = 0.65 for the regression that included 3 explanatoryvariables. Imagine that we decided to add an additional explanatory variable (like theplayers' previous playoff experience). When we run the regression with theadditional explanatory variable the R2 = 0.78 is for the regression. We can interpretthis asthe additional explanatory variable is significant at the 5% level.the additional explanatory variable has lowered the explained sum of squaresmeasure in the regression.the additional explanatory variable is related to player salary and does belong inthe regression.the additional explanatory variable is not related to player salary and does notbelong in the regression.

Given information: The coefficient of determination for the old model is R1 2 = 0.65. The…

Answered: Suppose that we performed an estimate…

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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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?
You may need to use the appropriate technology to answer this question. A regression analysis involving 45 observations relating a dependent variable and two independent variables resulted in the following information. ý = 0.406 + 1.3385X, + 2X2 The SSE for the above model is 43. When two other independent variables were added to the model, the following information was provided. ý = 1.9 – 3X + 12X2 + 4Xg + 8x, This model's SSE is 36. At a 0.05 level of significance, test to determine if the two added independent variables contribute significantly to the model. State the relevant null and alternative hypotheses. O Ho: One or more of the parameters is not equal to zero. H₂: B₁ = B₂= B3 =B4 = 0 O Ho: One or more of the parameters is not equal to zero. H₂: B3 =B4 = 0 O Ho: B3 = P4 = 0 H₂: None of the parameters are equal to zero. ⒸH₁: B3 =B₁ = 0 H: One or more of the parameters is not equal to zero. O Ho: B₁ = P₂ = B3 =B4 = 0 H: One or more of the parameters is not equal to zero. ✔ Find…
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The multiple regression describes how the mean value of y is related to the xi independent variables. The parameters ?i are used to describe how the mean value of y changes for a one-unit increase in xi when the other variables are held constant. The given estimated regression equation follows where x1 is the high-school grade point average, x2 is the SAT mathematics score, and y is the final college grade point average. ŷ = −1.38 + 0.0232x1 + 0.00482x2 If the variable x2 is held constant, then only changes in x1 will impact the predicted values of ŷ. Since the coefficient of x1 is positive, for each one-unit increase of x1, the values of ŷ will increase by the value of ?1, where ?1 = . In context, for each one point increase of the high-school grade point average, the final college grade point average will increase by this amount when the SAT mathematics score does not change. If the variable x1 is held constant, then only changes in x2 will impact the predicted values of ŷ. Since the…
A group of researchers measured how funny people rated a cartoon when they were in one of two groups: holding a pen in their teeth (forcing them to smile) or holding a pen in their lips (forcing them to frown). For this study, identify the independent variable and the dependent variable. Justify your response.
A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?
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 are the coefficients of correlation between miles per gallon and horsepower? Between miles per gallon and the weight of the car? What are the directions and strengths of these coefficients? Do the coefficients of correlation indicate a strong correlation, weak correlation, or no correlation between these variables? See Step 4 in the Python script. Write the multiple regression equation for miles per gallon as the response variable. Use weight and horsepower as predictor variables. See Step 5 in the Python script. How might the car rental company use this model?
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A negative correlation means that decreases in the X variable tend to be accompanied by decreases in the Y variable. T or F

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