QUESTION 8 The data given in the Table below is produced from a model of the form: Y = (aX+b) s. 4 2 X Y 1 1.58113883 2 1.73205081 1.87082869 5 2.12132034 6 2.23606798 2.34520788 8 2.44948974
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1. What is the value of a, b and s?
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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.Zipfs Law The following table shows U.S cities by rank in terms of population and population in thousands. City Rank r Population N New York 1 8491 Chicago 3 2722 Philadelphia 5 1560 Dallas 9 1280 Austin 11 913 San Francisco 13 852 Columbus 15 836 A rule known as Zipfs law tells us that it is reasonable to approximate these data with a power function. a Use power regression to express the population as a function of the rank. b Plot the data along with the power function from part a. c Phoenix is the sixth largest city in the United States. Use your answer from part a to estimate population of Phoenix. Round your answer in thousands to the nearest whole number. Note: The actual population is 1537 thousand.Question 5 Use the information attached to answer Question 5 and Question 6.The table below shows the sales (in packets) of a commodity at a supermarket over a three-year period, together with appropriate totals and values of a four - point moving average.Find the value of w.A. 127B. 246.5 C. 242D. 246 Question 6 Find the values of x and y?A. x = 483, y = 118.75B. x = 483, y = 59.375C. x = 241.5, y = 118.75D. x = 241.5, y =59.375
- Question 2 The following regression output was obtained. The regression model is Test scores onstudent teacher ratio. When your research assistant cut and pasted the results for you, therewere several vital pieces of information missing. See output below: SUMMARYOUTPUTRegression StatisticsMultiple R 0.226362751R Square (a)Adjusted R Square 0.048970335Standard Error 18.5809675Observations 420ANOVA df SS MS FRegression 1 7794.110041 7794.110041 22.57511055Residual 418 144315.4836 345.2523531Total 419 (b) Coefficients Standard Error t Stat P-valueIntercept 698.9329523 9.467491444str -2.279808287…Question 2 The following regression output was obtained. The regression model is Test scores onstudent teacher ratio. When your research assistant cut and pasted the results for you, therewere several vital pieces of information missing. See output below: SUMMARYOUTPUTRegression StatisticsMultiple R 0.226362751R Square (a)Adjusted R Square 0.048970335Standard Error 18.5809675Observations 420ANOVA df SS MS FRegression 1 7794.110041 7794.110041 22.57511055Residual 418 144315.4836 345.2523531Total 419 (b) Coefficients Standard Error t Stat P-valueIntercept 698.9329523 9.467491444str -2.279808287…Question 2: The estimated regression equation for a model involving two independent variables and 65 observations is: yhat = 55.17+1.1X1 -0.153X2 Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0, Sb1 = 0.33, Sb2 = 0.20.a. Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 65 and X2 = 70. c. Compute R-square and Adjusted R-Square. d. Comment on the goodness of fit of the model. e. Compute MSR and MSE. f. Compute F and use it to test whether the overall model is significant using a p-value (α = 0.05). g. Perform a t test using the critical value approach for the significance of β1.Use a level of significance of 0.05. h. Perform a t test using the critical value approach for the significance of β2.Use a level of significance of 0.05.
- Question #7 For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield x=6.4, y =6.0, r=−0.280, P-value=0.049, and y=8.19−0.338x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x=7. Use a 0.10 significance level. The best predicted value of y when x=7 ___________. (Round to one decimal place as needed.)question 32 Statistics students in Oxnard College sampled 10 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below: Number of Pages (xx) Cost(yy) 575 95.25 351 60.65 788 137.2 600 108 393 75.95 897 155.55 504 76.6 571 86.65 516 79.4 986 166.9 A student calculates a linear modely = __________x +_____________ . (Please show your answers to two decimal places)Use the model to estimate the cost when number of pages is 829.Cost = $___________- (Please show your answer to 2 decimal places.)Question 27 In March, Maggie collected the daily sales of ice-cream in Montreal (Y) and the outdoor temperature for each day (X). She computed the sample correlation coefficient between X and Y to be 0.1, and used the data to build a simple linear regression model Y = b + cX.
- Question 6 The tables show critical t values, then positive and negative z scores.Question 19: Based on the data shown below, a statistician calculates a linear model y=−2.23x+48.46y=-2.23x+48.46. x y 4 40.7 5 36.2 6 34.1 7 34.3 8 28.9 9 28.3 10 27.8 11 25.5 12 19.4 13 19.9 Use the model to estimate the y-value when x=4x=4y = Use the model to estimate the y-value when x=8x=8y =What type of model is presented below – Model 3. What impact do d_y and d_rs have on the dependent variable d_m_p? Model 3: OLS, using observations 1980:2-1999:3 (T = 78) Dependent variable: d_m_p Coefficient Std. Error t-ratio p-value const 0.0113971 0.00130078 8.7617 <0.0001 *** d_y −0.0106911 0.100221 −0.1067 0.9153 d_rs 0.00151462 0.00110613 1.3693 0.1751 d_rl 0.000127744 0.00141954 0.0900 0.9285 d_p −0.354204 0.093535 −3.7869 0.0003 *** Mean dependent var 0.007578 S.D. dependent var 0.004753 Sum squared resid 0.001399 S.E. of regression 0.004378 R-squared 0.195607 Adjusted R-squared 0.151531 F(4, 73) 4.437922 P-value(F) 0.002885 Log-likelihood 315.5363 Akaike criterion −621.0725 Schwarz criterion −609.2890 Hannan-Quinn −616.3554 rho 0.485424 Durbin-Watson 1.001216
