Chapter 6 Minitab Instructions
Uniform Probabilities
A. (Replicating Example 6.1b) From the menu choose Calc > Probability Distributions >
Uniform.
B. Choose Cumulative probability. Enter 2500 as the Lower endpoint and 5000 as the Upper
endpoint. Then select Input constant and enter 4000. Since Minitab returns a cumulative
probability, we calculate 1  P( X  4000) . Click OK.
C. Minitab shows the output below. Since P  X  4000  0.60 , we find
P  X  4000  1  0.60  0.40 .
Cumulative Distribution Function
Continuous uniform on 2500 to 5000
x
4000
P( X <= x )
0.6
1
Normal Probabilities
The Normal Transformation
A. (Replicating Example 6.8a) From the menu choose Calc > Probability Distributions >
Normal.
B. Choose Cumulative probability. Enter 12 for the Mean and 3.2 for the Standard deviation.
Select Input constant and enter 20. Since Minitab returns a cumulative probability, we
calculate 1  P( X  20) . Click OK.
C. Minitab shows the output below. Since P  X  20  0.9938 , we then find
P  X  20  1  0.9938  0.0062 .
Cumulative Distribution Function
Normal with mean = 12 and standard deviation = 3.2
x
20
P( X <= x )
0.993790
2
The Inverse Transformation
A. (Replicating Example 6.8c) From the menu choose Calc > Probability Distributions >
Normal.
B. Choose Inverse cumulative probability. Enter 12 for the Mean and 3.2 for the Standard
deviation. Select Input constant and enter 0.90. Minitab will solve for x in
P  X  x   0.90 . Click OK.
C. Minitab shows the output below; thus, P  X  16.10  0.90 .
Inverse Cumulative Distribution Function
Normal with mean = 12 and standard deviation = 3.2
P( X <= x )
0.9
x
16.1010
3
Exponential Probabilities
A. (Replicating Example 6.9b) Choose Calc > Probability Distributions > Exponential.
B. Choose Cumulative probability. Enter 25 for Scale (since Scale = E ( X )  25 ) and 0.0 for
Threshold. Select Input constant and enter 60. Since Minitab returns a cumulative
probability, we calculate 1  P( X  60) . Click OK.
C. Minitab shows the output below. Since P  X  60  0.9093 , we find
P  X  60  1  0.9093  0.0907 .
Cumulative Distribution Function
Exponential with mean = 25
x
60
P( X <= x )
0.909282
4