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- A1 How do I identify the order of differencing (d) for these ARIMA models? Any explanation for how to find d by looking at the equation like in this form would be appreciated. Thanks!Find the least-squares equation for the following pairs of data: x = earthquake magnitude 2.9 4.2 3.3 4.5 2.6 3.2 3.4 y = depth of earthquake (in km) 5 10 11.2 10 7.9 3.9 5.5 A. y = 2.16 + 0.221x B. y = 0.221 + 2.16x C. y = 2.16 + 0.312x D. y = 0.221 + 2.82xQuestion 9 of 10, Step 1 of 2 The following table lists the birth weights (in pounds), x, and the lengths (in inches), y, for a set of newborn babies at a local hospital. Birth Weights and Lengths Birth Weight (in Pounds), x 8 7 6 9 10 8 3 3 7 11 Length (in Inches), y 20 18 16 21 19 20 15 16 16 21 Step 1 of 2 : Find an equation of the least-squares regression line. Round your answer to three decimal places, if necessary.
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.3 8.6 7.1 3.3 2.4 2.3 2.4 0.7 yy 13.7 11.1 10.4 6.9 6.4 6.2 6.1 4.9 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.83x+4.28.y=0.83x+4.28. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 1.6 thousand automatic weapons?Answer = Round to 3 decimal places.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.3 8.6 7.1 3.3 2.4 2.3 2.4 0.7 yy 13.7 11.1 10.4 6.9 6.4 6.2 6.1 4.9 xx = thousands of…The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.9 8.1 6.9 3.8 2.3 2.7 2.4 0.7 yy 13.9 11.2 9.7 7.2 5.8 6.4 5.9 4.9 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.83x+4.08.y=0.83x+4.08. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 9 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4 thousand automatic weapons?Answer = Round to 3 decimal places.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.6 7.1 3.9 2.5 2.6 2.4 0.4 yy 14.3 11.5 9.8 7.6 6.2 6.5 6.4 4.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.86x+4.07.y=0.86x+4.07. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 3 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.1 thousand automatic weapons?Answer = Round to 3 decimal places.
- Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certainThe following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/ 24 hr). Predictor Coef SE Coef T P Constant 0.8678 0.4148 2.06 0.84 Weight 0.40889 0.02978 13.52 0.000 S = 0.517508 R-Sq = 98.0% (a) Write out the least-squares equation. y^ = ? + ?x (b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.) (c) What is the value of the correlation coefficient r? (Use 3 decimal places.)Given data points: (2,3), (3,4), (5,2), (6,5) and (7,3) indicate ln(y-C1) = C2+ ln x , using Least Square Method.Curve Fitting using the formula, (FT)(F)(C) = (FT)(y)F = matrixFT = transpose of matrixC = constanty = data given
- Which of the following is a valid reason for using nonparametric methods?A. To incorporate domain knowledge as a finite-dimensional model in the analysis. B. We are reluctant to assume strong conditions on the data.C. To have the best possible analytical result.D. None of the above.The following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/ 24 hr). Predictor Coef SE Coef T PConstant 0.8570 0.4148 2.06 0.84Weight 0.38243 0.02978 13.52 0.000 S = 0.517508 R-Sq = 97.4% (a) Write out the least-squares equation. y^= ______ + _____x (b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.)This problem finds the curve y=C + D * 2^t which gives the best least squares fit to the points (t,y) = (0,6) , (1,4) , (2,0). Find the coefficents C and D of the best curve y=C + D * 2^t