QUESTION 15If the least-squares regression line is y = 5 x-3, then for x = 3, the predicted value for y is:ⒸA. 0.OB. 1.20.OC. 2.OD. 12.

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Answered: QUESTION 15 If the least-squares…

Algebra and Trigonometry (6th Edition)

6th Edition

ISBN:9780134463216

Author:Robert F. Blitzer

Publisher:Robert F. Blitzer

ChapterP: Prerequisites: Fundamental Concepts Of Algebra

Section: Chapter Questions

Problem 1MCCP: In Exercises 1-25, simplify the given expression or perform the indicated operation (and simplify,...

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23:23 ..l ? YE 74 [Template] Sta.. Business Statistics Skill 2 Answer the following Questions. Each question carries 5 marks. (2*5=10) 1. Calculate Coefficient of correlation from the following data: 500 1000 1500 2000 2500 3000 3500 100 200 300 400 500 600 700 2. Obtain the regression equations for the following taking 42 and 58 as assumed mean. |X 10 25 34 42 37 35 36 45 Y 56 64 63 58 73 75 82 77
Question 8 please
When a stone is dropped in a pond, ripples are formed and travel in concentric circles away from where the stone was dropped. The equation of the least-squares regression line is log(Area) = 0.490 + 2.004 log(Time). WWhat is the predicted area of the circle, in cm2, 4 seconds after the stone is dropped? O 49.72 cm2 O 199.43 cm2 O 311.89 cm? O 1854.10 cm2
Question 4 Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of the company wants to know how different variables affect the sales of his vehicles. A random sample of yearly data was taken with the view to testing the model: SALES=a+BAGE+YMIL+&ENG Where SÄLES= amount that a vehícle is sold for($000's), AGE = age of the vehicle, MIL= the total mileage of the vehicle at the point of sale and ENG= the size of the engine. The sample of data was processed using MINITAB and the following is an extract of the output obtained: The regression equation is ***** Coef StDev t-ratio p-value Predict or Constan 1.7586 0.2525 6.9648 0.0000 AGE 0.2124 0.3175 0.5042 ** MIL -0.7527 0.3586 -2.0991 7.7664 0.0000 *** ENG 4.8124 Analysis of Variance DF MS Source 3 413.1291 138.709 **** 0.00 Regressi 7 on 50 457.7607 2.2888 Error Total 53 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values *', '**',…
Example3. Calculate Pearson's coefficient of skewness for the following data: X: 2 3 4 6. 7 f:1 3 13 8. 3
Let sale denote the sale price for a house, sqft its square footage, and days the number of days that it has been on the market. Consider running two different regressions: First regression: sale = B1 + B2sqft + ß3days + e Second regression: sale = Bi + B2sqft + e Which of the following statements is false? In the options below, the quantities SST, SSE, and SSR are as defined when we discussed R?, that is SST = E(Y, – Ỹ)², SSE = E(Y; - Ý )², and SSR = i=1 O a. The SST from the first regression can be strictly smaller than the SST from the second regression. O b. The SSE from the first regression can be strictly smaller than the SSE from the second regression. O c. The R- from the first regression can be strictly larger than the R2 from the second regression. O d. The R2 from the second regression is equal to the R2 from the regression sqft = Yi + Y2sale + e O e. The SSR from the first regression can be strictly larger than the SSR from the second regression.
In a regression analysis involving 25 observations, the following estimated regression equation was developed.ŷ = 10 – 18x1 + 3x2 + 14x3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296The multiple coefficient of determination is _____. a. .27 b. .73 c. .33 d. .50
X y 1 1 É Consider the following table of data. a. Calculate the least squares line and the correlation coefficient. b. Repeat part (a), but this time delete the last point. c. Draw a graph of the data, and use it to explain the dramatic difference between the answers to parts (a) and (b). a. The least squares line is Y= x +. (Use integers or decimals for any numbers in the equation. Round to four decimal places as needed.) 1 2 2 1 22 11 11
Question 12. Fit a regression line to the points (2, 7), (3, –3), (–2, 5).

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QUESTION 15 If the least-squares regression line is y = 5 x-3, then for x = 3, the predicted value for y is: O A. 0. OB. 1.20. OC. 2. OD. 12.