Consider the following data for a dependent variable y and two independent variables, ¤1 and x2. 12 29 12 94 47 10 109 24 17 113 51 17 178 41 95 52 19 176 75 8 171 36 12 118 59 13 143 77 16 211 The estimated regression equation for these data is ŷ = –16.20 + 1.90x1 + 4.93x2 Here SST = 15,059.6, SSR = 14,242.3, s = 0.2030, and Sin = 0.812? a. Test for a significant relationship among 21, 82, and y. Use a = 0.05. F = | (to 2 decimals) The p-value is - Select your answer - At a = 0.05, the overall model is - Select your answer b. Is B1 significant? Use a = 0.05 (to 2 decimals). Use t table.
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.The following table shows the annual expenditures, in dollars, per customer unit for residential landline phone services and cellular phone services in the United States in the given year.† Year Landline Cell 2004 592 378 2006 542 524 2008 467 643 2010 401 760 Calculate the regression line for each type of service. (Let t be the time in years since 2004, L be the operating revenue of landline phone services and C be the expenditure of cellular services. Round your regression parameters to two decimal places.) L(t) = C(t) = Determine the expenditure level at which the two lines cross. Round your answer for the expenditure level to one decimal place. million dollarsUse the following table to find the equation of the regression line, between x and y x312304y210342
- Consider the following data for two variables, x and y. x 9 32 18 15 26 y 9 19 20 15 22 Develop an estimated regression equation for the data of the form ŷ = b0 + b1x + b2x2. (Round b0 to two decimal places and b1 to three decimal places and b2 to four decimal places.) ŷ = (c) Use the model from part (b) to predict the value of y when x = 20. (Round your answer to two decimal places.)Consider the following data for two variables, x and y. x 22 24 26 30 35 40 y 11 21 34 36 39 36 Develop an estimated regression equation for the data of the form ŷ = b0 + b1x + b2x2. (Round b0 to one decimal place and b1 to two decimal places and b2 to four decimal places.) ŷ = (e) Use the results from part (d) to test for a significant relationship between x, x2, and y. Use ? = 0.05. Is the relationship between x, x2, and y significant? Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = (f) Use the model from part (d) to predict the value of y when x = 25. (Round your answer to three decimal places.)Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 6 11 13 Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. ŷ = (e) Use the estimated regression equation to predict the value of y when x = 2.
- Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y = annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid .The correlation between the two variables is .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…Consider the following regression equation representing the linear relationship between the Canada Child Benefit provided for a married couple with 3 children under the age of 6, based on their annual family net income: ŷ =121.09−0.57246xR2=0.894 where y= annual Canada Child Benefit paid (in $100s) x = net annual family income (in $1000s) Source: Canada Revenue Agency a. As the net annual family income increases, does the Canada Child Benefit paid increase or decrease? Based on this, is the correlation between the two variables positive or negative?The Canada Child Benefit paid ? .The correlation between the two variables is ? .b. Calculate the correlation coefficient and determine if the relationship between the two variables is strong, moderate or weak.r= , the relationship is ? . Round to 3 decimal places c. Interpret the value of the slope as it relates to this relationship. For every $1 increase in annual family net income, there is a $0.57246 decrease in…The grades of a sample of 9 students on a prelim exam (x) and on the midterm exam (y) are shown below. Find the regression equation. y = 34.661 + 0.433x y = 0.777 + 12.0623x y = 12.0623 + 0.777x y = 34.661 - 0.433x
- Consider the following regression equation: Y = 30 + 8X. If SSE = 720 and SS Total = 1,200, then the correlation coefficient is ________. A) −0.632B) 0.70C) 0.632D) −0.70The following estimated regression equation is based on 30 observations. ŷ = 18.3 + 3.9x1 − 2.2x2 + 7.5x3 + 2.5x4 The values of SST and SSR are 1,805 and 1,762, respectively. a. Compute R2 = (to 3 decimals). b. Compute Ra2 = (to 3 decimals).From 8 observations the following results were obtainedΣXΣ =544, ΣY =552, ΣXY = 37560, ΣX^2 =37028, ΣY^2 =38132. Find i) the correlation co- efficient, ii) and, state the relationship, iii) the regression line equation = Y=mX+bY=mX+b