solution :
a)option 1 is right answer
b) It appears linear relationship between x and y
c) option A is right answer
d)
linear regression eqation Y^= 2.5X +1.5
e) the estimated pridicted value Y^=2.5*3+1.5=9
the pridicted value is 9
Given are five observations for two variables, I and y. X1 1 2 3 4 5...
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 3 7 8 11 14 Which of the following scatter diagrams accurately represents the data? 1. 2. 3. SelectScatter diagram #1Scatter diagram #2Scatter diagram #3Item 1 What does the scatter diagram indicate about the relationship between the two variables? SelectThere appears to be a linear relationship between x and yThere appears to be a nonlinear relationship between x and yItem 2 Try to...
Li 1 2 3 4 5 Yi 4 5 5 11 13 a. Which of the following scatter diagrams accurately represents the data? --05. 05 5 3 -2,5-33,5.4-4,5. 5,5 00 05.. .. ...25... 3,5.4.45 5 5 5 0 , 5 1 , 5 2 ,5.. .3,5 4 4,5 5,5 - Select your answer - b. What does the scatter diagram indicate about the relationship between the two variables? - Select your answer - c. Try to approximate the relationship between...
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 3 8 6 12 14
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 3 7 5 11 14
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 3 8 5 10 14 (d) 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.
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Given are five observations for two variables, x and y.xi12345yi4761214Round your answers to two decimal places. Use Table 1 of Appendix B a. Using the following equation: b. Using the following expression: c. Using the following equation: d. Using the following expression:
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Given are five observations for two variables, x and y. xi 3 12 6 20 14 yi 50 45 55 15 15 (d) 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 = 9. Observation 1 2 3 4 5 6 7 8...