Question

In: Statistics and Probability

Complete parts​ (a) through​ (c) using the following data. Row 1 2 2 2 5 5...

Complete parts​ (a) through​ (c) using the following data.

Row 1 2 2 2 5 5 5 5 6 7 7
Row 2 92 82 83 79 90 73 79 82 59 70 ​

Construct a scatter plot of the data and draw the regression line. Plot Row 1 on the horizontal axis and Row 2 on the vertical axis.

(a) Find the equation of the regression line for the given​ data, letting Row 1 represent the​ x-values and Row 2 the​ y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line when Row 1 represents the​ x-values.

​(Round to three decimal places as​ needed.)

​(b) Find the equation of the regression line for the given​ data, letting Row 2 represent the​ x-values and Row 1 the​ y-values.

Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line when Row 2 represents the​ x-values.

y = x( ) +( )

​(Round to three decimal places as​ needed.)

Solutions

Expert Solution

X y (x-xbar)^2 (x-xbar)(y-ybar)

2
2
2
5
5
5
5
6
7
7

M: 4.6

92
82
83
79
90
73
79
82
59
70

M: 78.9

6.76
6.76
6.76
0.16
0.16
0.16
0.16
1.96
5.76
5.76

SS: 34.4

-34.06
-8.06
-10.66
0.04
4.44
-2.36
0.04
4.34
-47.76
-21.36

SP: -115.4

a) regression equation

  Sum of X = 46
Sum of Y = 789
Mean X = 4.6
Mean Y = 78.9
Sum of squares (SSX) = 34.4
Sum of products (SP) = -115.4

Regression Equation = ŷ = bX + a

b = SP/SSX = -115.4/34.4 = -3.355

a = MY - bMX = 78.9 - (-3.35*4.6) = 94.331

ŷ = -3.355X + 94.331

Scatter plot

B) Sum of X = 789
Sum of Y = 46
Mean X = 78.9
Mean Y = 4.6
Sum of squares (SSX) = 840.9
Sum of products (SP) = -115.4

Regression Equation = ŷ = bX + a

b = SP/SSX = -115.4/840.9 = -0.137

a = MY - bMX = 4.6 - (-0.14*78.9) = 15.428

ŷ = -0.137X + 15.428

Scatter diagram


Related Solutions

Complete parts​ (a) through​ (c) using the following data. Row 1 Row 2 2 93 2...
Complete parts​ (a) through​ (c) using the following data. Row 1 Row 2 2 93 2 87 2 79 5 78 5 95 5 66 6 74 6 84 7 56 8 62 (a) Find the equation of the regression line for the given​ data, letting Row 1 represent the​ x-values and Row 2 the​ y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line...
Complete parts​ (a) through​ (c) using the following data. Row 1 1 2 2 2 2...
Complete parts​ (a) through​ (c) using the following data. Row 1 1 2 2 2 2 2 6 6 6 8 Row 2 94 85 86 71 94 65 74 87 60 62 ​(a) Find the equation of the regression line for the given​ data, letting Row 1 represent the​x-values and Row 2 the​ y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line when...
Complete parts (a) through (c) using the following data. Row 1: 1 3 3 4 4...
Complete parts (a) through (c) using the following data. Row 1: 1 3 3 4 4 4 5 6 6 7 Row 2: 90 82 76 76 90 72 80 90 55 70 A.) Find the equation of the regression line for the given data, letting Row 1 represent the x-values and Row 2 the y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line...
Use the data in the table below to complete parts (a) through (c). X: 5 5...
Use the data in the table below to complete parts (a) through (c). X: 5 5 6 9 13 16 18 48 Y: 30 27 18 23 25 20 21 10 A.) Construct a scatterplot of the data. B.) Indentify any possible outliners. A.) The point (18,21) may be an outliner. B.) The point (48,10) may be an outliner C.) The point (5,27) may be an outliner. D.) The point (5,30) may be an outliner E.) There are no outliners....
5. Use the given data set to complete parts​ (a) through​ (c) below.​ (Use a=0.05.) x             ...
5. Use the given data set to complete parts​ (a) through​ (c) below.​ (Use a=0.05.) x              y 10           7.45 8              6.77 13           12.75 9              7.11 11           7.81 14           8.84 6              6.08 4              5.39 12           8.14 7              6.43 5              5.73 a. Construct a scatterplot Find the linear correlation​ coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=_____. ​(Round to three decimal places as​...
Consider the following set of ordered pairs. Complete parts a through c. x 1 1 3...
Consider the following set of ordered pairs. Complete parts a through c. x 1 1 3 3 1    y −1 1 4 3 −1 a. Calculate the slope and​ y-intercept for these data. ^y=______ + (______) x ​(Round to four decimal places as​ needed.) b. Calculate the total sum of squares​ (SST). SST= ​(Round to one decimal place as​ needed.) c. Partition the sum of squares into the SSR and SSE. SSE= ​(Round to three decimal places as​ needed.)...
1) Use the following information from a multiple regression analysis to complete parts​ (a) through​ (c)...
1) Use the following information from a multiple regression analysis to complete parts​ (a) through​ (c) below. n =25    b1 =30    b 2 =10    Sb1=8    Sb 2 =6 b) Construct a​ 95% confidence interval estimate of the population​ slope, β1. ____≤β1≤_____ ​(Round to four decimal places as​ needed.) c) At the 0.05 level of​ significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these​ results, indicate the independent variables to include...
Use the given data set to complete parts (a) through (c) below. (Use α = 0.05.)
Use the given data set to complete parts (a) through (c) below. (Use α = 0.05.) x1081391114641275y9.148.158.748.779.278.116.123.099.147.254.73Click here to view a table of critical values for the correlation coefficient. b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= _______ (Round to three decimal places as needed.) Using the linear correlation coefficient found in the previous step, determine whether there is sufficient...
For the data and sample regression equation shown​ below, complete parts​ (a) through​ (c). x 0...
For the data and sample regression equation shown​ below, complete parts​ (a) through​ (c). x 0 3 5 5 5      ModifyingAbove y with caret equals 4.500 minus 0.917 xy=4.500−0.917x y 4 3 0 −2 1 a. Determine the standard error of the estimate. b. Construct a residual plot. c. Construct a normal probability plot of the residuals. LOADING... Click the icon to view the table of normal scores.
Use the given data set to complete parts (a) through (c) below. (Use alphaαequals= 0.05.) x...
Use the given data set to complete parts (a) through (c) below. (Use alphaαequals= 0.05.) x 10 8 13 9 11 14 6 4 12 7 5 y 7.45 6.77 12.75 7.11 7.82 8.83 6.07 5.39 8.15 6.43 5.74 Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT