The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x, - 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,809 and 1,757, respectively.
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Q: The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 +…
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Q: The following estimated regression equation based on 10 observations was presented. ý = 29.1260 +…
A: Given : n = 10 y^=29.1260+0.5105x1+0.4680x2SST=6715.125SSR=6229.375We want find,SSE=?R2=?Ra2=?
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A: Given: n=5, ∑x=15, ∑y=20, ∑x-x2=10, ∑y-y2=26 and ∑x-xy-y=13. Then,x=∑xn=155=3y=∑yn=205=4
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A: given n = 30 observation y⏞ =17.2 +3.6 x1 - 2.2x2 + 7.8 x3 -2.9x4 The values of SST and SSR are…
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Q: The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1…
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Q: The following estimated regression equation based on 10 observations was presented. ŷ = 29.1260 +…
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Q: he admissions officer for Clearwater College developed the following estimated regression equation…
A: Given Information: The admissions officer for Clearwater college developed the following estimated…
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- The following results are from data concerning the amount withdrawn from an ATM machine based on the amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for females and = 0 for males) and an interaction term, SECONDS*FEMALE Based on the regression results, if a male and female each spend the same amount of time at the ATM machine (say 27 seconds), how much more (or less) will a male withdraw? (if a male withdraws more then your answer should be a positive number and if a male withdraws less then your answer should be a negative number? (please express your answer using 1 decimal places)Suppose the following data were collected from a sample of 5 car manufacturers relating monthly car sales to the number of dealerships and the quarter of the year. Use statistical software to find the following regression equation: SALESi= b0 + b1DEALERSHIPSi + b2 QUARTER1i+ b3QUARTER2i + b4QUARTER3i+ ei Is there enough evidence to support the claim that on average, car sales are higher in the 4th quarter than in the 2nd quarter at the 0.01 level of significance? If yes, write the regression equation in the spaces provided, rounded to two decimal places. Else, select "There is not enough evidence." Monthly Sales Number of Dealerships 1st Quarter (1 if Jan.-Mar., 0 otherwise) 2nd Quarter (1 if Apr.-Jun., 0 otherwise) 3rd Quarter (1 if Jul.-Sep., 0 otherwise) 4th Quarter (1 if Oct.-Dec., 0 otherwise) 85482 4 1 0 0 0 101319 9 1 0 0 0 121389 12 1 0 0 0 133677 18 1 0 0 0 194588 22 1 0 0 0 82128 4 0 1 0 0 150407 9 0 1 0 0 242714 12 0…For the 2011 season, suppose the average number of passing yards per attempt for a certain NFL team was 6.1. Use the estimated regression equation developed in part (c) to predict the percentage of games won by that NFL team. (Note: For the 2011 season, suppose this NFL team's record was 7 wins and 9 losses. Round your answer to the nearest integer.)
- You spilled water on your calculations from (a) and can't remember what your estimated regression parameters are. But you do have two possible estimated errors for each of your initial four observations:Assume a person got score of 32.5 on Test A and a score of 95.25 on Test B. Using the regression equation (B' = 2.3A + 9.5), what is the error of prediction for this person?The estimated regression equation for a model involving two independent variables and 10 observations follows.
- The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade be?What is the effect of this violation on the regression model? "The number of observations n is less than or equal to the number of parameters to be estimated"A multiple linear regression model based on a sample of 13 weeks is developed to predict standby hours based on the total staff present and remote hours. The SSR is 23,638.17 and the SSE is 33,273.99. a. Determine whether there is a significant relationship between standby hours and the two independent variables (total staff present and remote hours) at the 0.05 level of significance. What are the correct hypotheses to test?
- .The worker has noticed that the more time he spends at work (x), the less money he is likely to make (y) in conducting transactions for his firm. Which of the regression equations MOST suggests such a possibility?The Life Insurance Company is attempting to model the weight, Y (in pounds), of a random sample of n=92 randomly selected adults using height, X1 (in inches), and gender, I2 (0 = Male 1=Female). In addition, as part of the research objective, we also wish to determine if the influence of height (X1) on weight (Y) depends on gender (I2) and vice versa. Write out the general regression equation for this model, based on the research objectives and information provided. Using the general equation from part A, write out the specific regression equation for a female. Using the general equation from part A, write out the specific regression equation for a male. If it was found that the influence of height on weight did NOT depend on gender, how would this change the equation given in part A of this problem? Rewrite the general equation from part A here.In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 For this estimated regression equation, SST = 1,855 and SSR = 1,810. 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.) Suppose variables x1 and x4 are dropped from the model and the following estimated regression equation is obtained. ŷ = 11.1 − 3.6x2 + 8.1x3 For this model, SST = 1,855 and SSR = 1,755. (b)Compute SSE(x1, x2, x3, x4). SSE(x1, x2, x3, x4) (c)Compute SSE(x2, x3). SSE(x2, x3)= (d)Use an F test and a 0.05 level of significance to determine whether x1 and x4 contribute significantly to the model. 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 =