Data Set:{(−3,4), (−2, 3), (−1, 3), (0, 7), (1, 5), (2, 6), (3, 1)}1. The regression line is: y = -2FS0.3Your Turn: Data Set 22. Based on the regression line, we would expect thevalue of response variable to be 0.0054. If x= -3.5, the y = 1when the explanatory variable is 0.3. For each increase of 1 in of the explanatory variable,we can expect a(n) decreaseof 1in the response variable.ovemple ofF6evtrannlationXO SearchMALERINION8*. This is angprt schome

As per policy I have calculated 3 subparts kindly REPOST for remaining. Here given 7 pair of data x…

Answered: 1. The regression line is: y = -2 0.3 x…

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 real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 – 2.5 x2, to predict y = the market price of a home (in $1,000s), using independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. The regression coefficient of x2 suggests this: __________. If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homes If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homes
I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
The flow rate in a device used for air quality measurement depends on the pressure drop x (inches of water) across the device's filter. Suppose that for x values between 5 and 20, these two variables are related according to the simple linear regression model with true regression line y = -0.11 + 0.097x. (a.1) What is the true average flow rate for a pressure drop of 10 in.?(a.2) A drop of 15 in.?(b) What is the true average change in flow rate associated with a 1 inch increase in pressure drop?(c) What is the average change in flow rate when pressure drop decreases by 5 in.?
A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.
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…
| Find the regression lines of Y on X and X on Y for the following data. EX = 70, EY = 83, EX? = 590, EY² = 755, EXY= 640, n= 10.
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…
The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.
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3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
You decide to add a second independent variable to your regression. Male is a dummy variable that equals 1 if the individual is male and 0 otherwise. Your regression results are now: wage = 3.071 + 0.289 × Years of Schooling + 1.28 × Male (0.143) (0.0168) (0.624) Interpret the coefficients from this regression. Make sure to clearly indicate what is changing and what is constant in each interpretation. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.316. Interpret the meaning of this value.
The sales of a company (in million dollars) for each year shown in the table below (25)X(year) 2005 2006 2007 2008 2009Y (sales) 12 19 39 37 45a. Find the regression line of the data. Draw the inference about the dataset.b. Use the regression line as a model to estimate the sales of the company in 2012.

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1. The regression line is: y = -2 0.3 x x X - 2. Based on the regression line, we would expect the value of response variable to be 0.005 x when the explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) decrease ✓ of 1 x in the response variable.