Minitab Cheat Sheet for Statistical Analyses
Ztests and Zintervals for One proportion
To calculate a confidence interval and perform a hypothesis
test for a single population proportion when you have summarized
data:
 Select Stat. Select Basic Statistics. Select 1 Proportion.
 Click on the button in front of Summarized data. Type in n, the
number in the random sample, in the box labeled Number of trials. Type
in X, the number of successes, in the box labeled Number of successes.
 Click on Options... In the box after Confidence Level, type
your desired confidence level. In the box after Test Proportion,
specify the value of the proportion in your null hypothesis. Under Alternative,
select the desired direction of your alternative hypothesis. Click on
box before Use test and interval based on normal distribution. Select
OK.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.1.8.
Test and Confidence Interval for One Proportion
Test of p = 0.75 vs p < 0.75
Sample X N Sample p 95.0 % CI ZValue PValue
1 273 390 0.700000 (0.654519, 0.745481) 2.28 0.011

Sample Size Calculations for Tests about One Population Mean
 Select Stat. Select Power and Sample Size. Select 1 Sample
Z.
 Click on the button in front of Calculate sample size for each power
value.
 In the box labeled Power values, type the desired power.
 In the box labeled Difference, type the difference in the null hypothesis
and the value of the mean in the alternative hypothesis that is meaningfully
different from the null. The difference should be alternative minus null.
 Select Options.... Click on the the desired Alternative Hypothesis,
and specify the desired Significance level. Select OK.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.2.7.
1Sample Z Test
Testing mean = null (versus < null)
Calculating power for mean = null  65
Alpha = 0.05 Sigma = 140
Sample Target Actual
Size Power Power
40 0.9000 0.9017

1sample t
To calculate a confidence interval or perform a hypothesis test for
a single population mean:
 Select Stat. Select Basic Statistics. Select 1Sample
t.
 The 1Sample t PopUp Window will appear. In the left box, click
once on the variable you want analyzed. Click once on the Select button.
The column name (or variable name) will appear in the box labeled Variables.
 To create a confidence interval: By default, the radio button before
Confidence Level should be selected. If it is not, click on it to select
it. In the box after Confidence Level, type the level of the confidence
interval that you desire. Ninetyfive percent (95%) is the default level.
 To perform a hypothesis test: Click on the radio button before
Test Mean. In the box after Test Mean, type the value of the mean in
the null hypothesis. Under Alternative, select the desired direction
of your alternative hypothesis. The choices are Not Equal, Less Than,
or Greater Than.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.3.10.
Test of mu = 125.00 vs mu not = 125.00
Variable N Mean StDev SE Mean T P
torque 15 127.67 9.60 2.48 1.08 0.30

Twosample ttintervals and ttests
To calculate a confidence interval or perform a hypothesis test for the difference
in the means from two independent populations:
 Enter the data into two separate columns.
 Select Stat. Select Basic Statistics. Select 2Sample t.
 The 2Sample t PopUp Window will appear. Click on the button in
front of Samples in different columns. Specify one of your samples
as the First sample and your other sample as the Second sample.
 To perform a hypothesis test, under Alternative, select the desired
direction of your alternative hypothesis. The choice will depend on
which sample you specified as your First sample and which sample you specified
as your second sample. Minitab always considers the First mean minus the Second
mean.
 In the box after Confidence Level, type the level of the confidence
interval that you desire. Ninetyfive percent (95%) is the default level.
 If appropriate, click on the box before Assume Equal Variances.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.4.3. Note that the
line Both use Pooled StDev means that we have assumed equal variances.
Both refers to both the confidence interval and the hypothesis test. Notice
the degrees of freedom are 20.
Two sample T for straw vs blue
N Mean StDev SE Mean
straw 9 21.033 0.606 0.20
blue 13 20.89 1.01 0.28
95% CI for mu straw  mu blue: ( 0.65, 0.93)
TTest mu straw = mu blue (vs not =): T = 0.37 P = 0.71 DF = 20
Both use Pooled StDev = 0.869

This is what the output looks like if we don't assume equal variances. Note
that there is no Both use Pooled StDev line, and the degrees of freedom have
been adjusted downward to 19.
Two sample T for straw vs blue
N Mean StDev SE Mean
straw 9 21.033 0.606 0.20
blue 13 20.89 1.01 0.28
95% CI for mu straw  mu blue: ( 0.58, 0.86)
TTest mu straw = mu blue (vs not =): T = 0.41 P = 0.69 DF = 19

Paired ttest and Paired tintervals
To calculate a confidence interval or perform a hypothesis test for the difference
in the means from two dependent populations:
 Select Stat. Select Basic Statistics. Select Paired t.
 The Paired t PopUp Window will appear. Specify your First Sample.
Specify your Second Sample.
 Click on Options... In the box after Confidence Level,
type your desired confidence level. In the box after Test Mean,
specify the value of the mean in your null hypothesis. Under Alternative,
select the desired direction of your alternative hypothesis. Select
OK.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.3.18.
Paired T for ballA  ballB
N Mean StDev SE Mean
ballA 17 256.18 18.70 4.54
ballB 17 251.41 14.93 3.62
Difference 17 4.76 9.09 2.20
95% CI for mean difference: (0.09, 9.44)
TTest of mean difference = 0 (vs > 0): TValue = 2.16 PValue = 0.023

Chisquare test for homogeneity and/or test for independence
Assuming you have a table of summarized data:
 Enter the table of summarized data into Minitab.
 Select Stat. Select Tables. Select Chisquare test.
 Specify the columns containing the table of summarized data.
 Select OK. The output will appear in the Session Window.
Example
The following is the Minitab output for Exercise #7.6.2.
Data Display
Row Cat1 Cat2 Cat3 Cat4 Cat5 Cat6
1 95 36 71 21 45 32
2 53 26 43 18 32 28
3 130 75 136 33 61 65
ChiSquare Test
Expected counts are printed below observed counts
Cat1 Cat2 Cat3 Cat4 Cat5 Cat6 Total
1 95 36 71 21 45 32 300
83.40 41.10 75.00 21.60 41.40 37.50
2 53 26 43 18 32 28 200
55.60 27.40 50.00 14.40 27.60 25.00
3 130 75 136 33 61 65 500
139.00 68.50 125.00 36.00 69.00 62.50
Total 278 137 250 72 138 125 1000
ChiSq = 1.613 + 0.633 + 0.213 + 0.017 + 0.313 + 0.807 +
0.122 + 0.072 + 0.980 + 0.900 + 0.701 + 0.360 +
0.583 + 0.617 + 0.968 + 0.250 + 0.928 + 0.100 = 10.176
DF = 10, PValue = 0.425
