Minitab Quick Reference
I.
Describing and analyzing categorical (qualitative) data
To produce tally for one categorical variable:
1. Stat>Tables>Tally.
2. Select the variable you want to summarize by double clicking it
3. Under Display, click on the appropriate box(es) to select the
statistics that you want calculated
4. Select OK. The output will appear in the session window.
To produce contingency table (cross tabulation) for two categorical
variables:
1. Stat>Tables>Cross Tabulation
2. Select the variables you want to summarize by double clicking
on them (if one variable can be designated as explanatory and
the other response, it is customary to define the rows using the
explanatory variable and the columns using the response
variable)
3. Under Display, click on the appropriate box(es) to select the
statistics that you want calculated
4. Select OK. The output will appear in the session window.
To test whether two categorical variables are independent:
1. Stat>Tables>Chi-Square Test
2. Select the variables you want analyzed by double clicking on
them
3. Select OK
To create a bar graph for a categorical variable:
1. Graph>Chart
2. Specify the categorical variable in the X text for Graph 1
3. Select OK.
If you want to show subgroups within the groups on the x-axis, click
on options and select clustering or stacking. Enter the categorical
variable for the subgroups. Clustering shows each subgroup as a
separate bar. Stacking shows subgroups as blocks stacked on top of
each other.
To create a pie chart for a categorical variable:
1. Graph > Pie Chart
2. Specify the categorical variable in the Chart data in text box
3. Select OK.
To make inferences (test and confidence interval) about one
population proportion:
1. Stat > Basic Statistics > 1 Proportion
2. Dialog box items :
a. Samples in columns: Enter the column(s) containing the
sample data. Each cell of these columns must be one of two
possible values and correspond to one item or subject. The
possible values in the columns must be identical if you
enter multiple columns.
b. Summarized data: You can enter summary data if they are
in that form.
3. Click on Options … In the Confidence Level text box, type
your desired confidence level. In the Test proportion text box,
specify the value of the proportion in the null hypothesis. In
Alternative text box, select the desired alternative hypothesis
from : not equal, less than, greater than.
4. Click on the box before Use test and interval based on normal
distribution if you want to use the normal approximation to
Binomial distribution.
5. Select OK.
6. Select OK.
To make inferences (test and confidence interval) about two
independent population proportions:
1. Stat > Basic Statistics > 2 Proportions
2. Dialog box items:
a. Sample in one column: Choose if you have entered raw
data into a single column with a second column of
subscripts identifying the sample.
b. Samples in different columns: Choose if you have entered
raw data into single columns for each sample.
c. Summarized data: Choose if you have summary values for
the number of trials and successes.
3. Click on Options … In the Confidence Level text box, type your
desired confidence level. In the Test difference text box, specify
the value of the difference in the null hypothesis. In Alternative
text box, select the desired alternative hypothesis from: not equal,
less than, greater than.
4. Select OK.
5. Select OK.
II.
Describing and analyzing quantitative data
To calculate descriptive statistics:
1. Stat > Basic Statistics > Display Descriptive Statistics
2. Specify the quantitative variable in the Variable text box
3. Select OK.
To create a dot plot:
1. Graph > Dotplot
2. Double click on the quantitative variable you want to plot
3. By default, the radio button in front of No Grouping is selected
and that will create one dotplot.
4. If you want to create a dot plot for different groups and your
groups are in different columns, then click on the radio button in
front of "Each column constitutes a group." If you want to create
a dot plot for different groups and your group variable is in one
column and the data in another column, click on the radio button
in front of By Variable. Then, click on the box after By
Variable. In the left box, click once on your grouping variable.
Click on the Select button. The column name (or variable name)
will appear in the box labeled By Variable.
5. Select OK. A new graph window, which contains the dotplot(s),
will appear.
To create a histogram:
1. Graph > Histogram
2. Double click on the quantitative variable you want analyzed. (If
you would like a relative frequency histogram rather than the
default frequency histogram, click on Options. Click on Percent.
Select OK.)
3. Select OK. A new graph window, which contains the histogram,
will appear.
To create a boxplot:
1. Graph > Boxplot
2. Double click on the quantitative variable you want analyzed. The
column name (or variable name) will appear under the Y in the
box labeled Graph Variables. If you would like to create a graph
that shows side-by-side boxplots, similarly select a categorical
variable to enter under the X in the box labeled Graph Variables.
3. Select OK. A new graph window, which contains the boxplot(s),
will appear.
To create a stem-and-leaf diagram:
1. Graph > Stem-and-leaf
2. Specify the quantitative variable you want analyzed in the
Variables text box.
3. Select OK. The output will appear in the Session Window.
To check whether the data follows a normal distribution:
1. Graph > Probability Plot
2. Specify the variable you want to check for normality
3. Select OK
To make inferences (test and confidence interval) about the difference
in the means of two independent populations
1. Stat > Basic Statistics > 2-sample t
2. Dialog box items:
a. Samples in one column: Choose if the sample data are in a
single column, differentiated by subscript values (group
codes) in a second column.
b. Samples in different columns: Choose if the data of the two
samples are in separate columns.
c. Assume equal variances: Check to assume that the
populations have equal variances. The default is to assume
unequal variances.
3. Click on Options … In the Confidence Level text box, type
your desired confidence level. In the Test difference text box,
specify the value of the difference in the null hypothesis. In
Alternative text box, select the desired alternative hypothesis
from: not equal, less than, greater than.
4. Select OK.
5. Select OK.
To make inferences (test and confidence interval) about the difference
in the means of two dependent populations
1. Stat > Basic Statistics > Paired t
2. Click in the First sample textbox and specify the data from the
first population. Click in the Second sample textbox and specify
the data from the second population.
3. Click on Options … In the Confidence Level text box, type
your desired confidence level. In the Test mean text box,
specify the value of the difference in the null hypothesis. In
Alternative text box, select the desired alternative hypothesis
from: not equal, less than, greater than.
4. Select OK.
5. Select OK.
To make inferences (test and confidence interval) about the means of
three or more independent populations
1. Stat > ANOVA > Oneway
2. Click in the column containing the response in the Response text
box and the column containing the factor levels in the Factor
text box.
3. Select OK.
To plot two quantitative variables (scatterplot)
1. Graph > Plot
2. Click in the Y textbox and specify the variable you want to put in
the vertical axis. Click in the X textbox and specify the variable
you want to put in the horizontal axis.
3. Select OK.
To plot two quantitative variables with fitted line
1. Stat > Regression > Fitted Line Plot
2. Click in the Response textbox and specify the response variable.
Click in the Predictors textbox and specify the variable you
want to put in the predictor variable.
3. Choose linear if you want to fit a straight line.
4. Select OK.
To analyze relationship between two or more variables
1. Stat > Regression > Regression
2. Click in the Response textbox and specify the response variable.
Click in the Predictors textbox and specify the explanatory
variable(s).
3. Select OK.
To find the correlation coefficient between two variables
1. Stat > Basic Statistics > Correlation
2. Click in the Variables textbox and specify the variables.
3. Select OK.
III.
Calculations
To perform calculations
1. Calc > Calculator
2. Name the variable you want to Store the results
3. Specify the expression
4. Select OK
To make patterned text data
1. Calc > Make Patterned Data > Text values
2. Type the name you want to call the column in the Stored
patterned data in textbox
3. Type the base pattern for the text
4. Enter the number of times you want to repeat each text value
within the sequence in the List each value textbox and enter the
number of times you want to repeat the entire sequence in the
List the whole sequence textbox
5. Select OK
To obtain a simple random sample
1. Calc > Random Data> Sample from Columns
2. Indicate the number of rows you want to sample from which
columns and where to store the data
3. Check the box sample with replacement if that is what you
want. The default is sample without replacement
4. Select OK
To obtain a random sample from a Bernoulli distribution
1. Calc > Random Data> Bernoulli
2. Indicate the number of rows of random data you want to generate
3. Specify storage column(s) for the generated values
4. Specify the probability of success
5. Select OK
To obtain probability distributions
1. Calc > Probability Distributions > then select the distribution you
want.
2. Choose Cumulative probability if you want to find the
probability of the random variable has a value less than or equal
to the value you specify. Choose probability density if you want
that for the value you specify. Choose Inverse cumulative
probability if you want to find the value associated with the
cumulative probability you specify. For example, if you specify
the probability as .9, then the Inverse cumulative probability will
give you the 90th percentile.
3. Choose input column or input constant according to the type of
input you have
4. Select OK