Leaning Tower of Pisa
Find a 90% confidence interval.
Year 75 77 78 80 81 82 83 84 85 87
Lean 642 656 667 688 696 698 713 717 725 757

Leaning Tower - Excell
Coefficie nts
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Intercept -42.4091
32.95436
-1.2869
0.234113
-118.402
33.5838
Year 9.092476
0.40545
22.42566
1.65E-08 8.157508
10.02745
Regression Statistics
Multiple R 0.99214
0.984342
R Square
Adjusted R
Square
Standard Error
Observations
0.982384
4.579967
10

Leaning Tower - Minitab
Predictor Coef SE Coef T P
Constant -42.41 32.95 -1.29 0.234
Year 9.0925 0.4054 22.43 0.000
S = 4.57997 R-Sq = 98.4% R-Sq(adj) = 98.2%

The following data is based on x (height in inches) and y (weight in lb) based on a sample of 10. Find a 90% confidence interval to estimate the slope.
Predictor Coef SE Coef T P
Constant -104.46 43.75 -2.39 0.044
Height 3.9527 0.6580 6.01 0.000
S = 7.16009 R-Sq = 81.9% R-Sq(adj) = 79.6%

The following data is based on x (height) and y (weight).
Is there a relationship?
Predictor Coef SE Coef T P
Constant -104.46 43.75 -2.39 0.044
Height 3.9527 0.6580 6.01 0.000
S = 7.16009 R-Sq = 81.9% R-Sq(adj) = 79.6%

The following is the regression analysis of y = maximum benchpress (MAX) and x = # of 60-pound Bench Presses (BP). Find a 95% CI. Use n = 10
Predictor
Constant
BP
R-Sq = 64.3%
Coef
63.537
1.4911
SE Coef
1.956
0.15
T
32.48
9.96
P
0.000
0.000

The following is the regression analysis of y = maximum benchpress (MAX) and x = # of 60-pound Bench Presses (BP). Are they related? Use n = 10
Predictor
Constant
BP
R-Sq = 64.3%
Coef
63.537
1.4911
SE Coef
1.956
0.15
T
32.48
9.96
P
0.000
0.000

The following shows they car weight (in lb) and the mileage (mpg) of 25 different models.
Predictor
Constant
BP
R-Sq = 64.3%
Coef SE Coef T
45.656
2.603
17.54
-0.0052
0.00062
-8.33
1. Give the prediction equation.
P
0.000
0.000
2. State & interpret the slope & y-int

The following shows they car weight (in lb) and the mileage (mpg) of 25 different models.
Predictor
Constant
BP
R-Sq = 64.3%
Coef SE Coef T
45.656
2.603
17.54
-0.0052
0.00062
-8.33
1. What is the correlation coefficient?
P
0.000
0.000
2. Estimate
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