"A BASIC GUIDE TO MINITAB" published by Bashir Ul Haq

Presented by: Bashir Ul Haq; +92342 0585558; haq7576@gmail.com

PUBLISHED BY:
BASHIR UL HAQ
UNIVERSITY OF MALAKAND
DEPARTMENT OF STATISTICS
+92342 0585558
haq7576@gmail.com

Introduction to Minitab
 statistical analysis is an important part of almost all scientific and
technical research work. Statistical techniques involve many tedious
computations. In addition visual presentation of large quantities of data is a
fundamental part of statistical reasoning.
 Computers are ideal ffor performing statistical calculations and
analysis. A person rarely need to write his or her own computer program.
Since they already exist almost all aspects of statistics. The most commonly
used programs for statistical work obtained from statistical software
packages. There are a lot of statistical software packages are currently
available. Among which Minitab is one of the popular and powerful software.
 actually the word “Minitab” is a registered trademark of Minitab . Minitab
windows is a powerful statistical software package that provide a wide range
and advanced data analysis capabilities .

Features of Minitab
Minitab for windows offers you the following features:
 Comprehensive statistics capabilities, including basic statistics, regression,
analysis of variance, non-parametrics, time series, cross-tabulations and
probability distribution.
 High resolution graphics, including 3D graphs.
 Quality control and improvement features, including probability plots.
 Design of experiments capabilities , allow you to generate and analyze full
and fractional designs etc
 Powerfull data management capabilities which allow you to input data from
other versions of minitab, spreadsheets, databases etc

MINITAB ENVIREMENT
Minitab for windows gives you a complete data analysis envirement .
Everything about your work is contained in a Minitab Project file. The project
file contains:
 DATA WINDOW or WORKSHEEET
Minitab places the data that you either enter or open from a file into a temporary storage area called the data window or
worksheet,
which like a spreadsheet, in which each column represents a variable and row represents the individual cases
 Session window:
The session window displays the statistical output requested. Most of what you command Minitab to do will appear here.
 History window:
The history window keeps track of all commands you have issued.
 Graph window:
The graph window exhibit the graphs you requested. The maximum numbers of graphs that ca be open at any time is 15.
 Info window:
The Info window summarizes each open worksheet

MENUS AND TOOLS
 Menu bar:
The menu bar is a starting point for selecting commands.
 Toolbar:
Minitab’s Toolbars are a quick way to issue Minitab commands: just click on a
tool button perform an action or open a dialog box.
 Status bar:
The status bar shows an explanation or helpful message when you point at a
menu item.

1: How to take subset worksheet from
the current data work sheet?
 Type or import the data into data window named worksheet 1…
 Go to menu, click on “Data” and then click on subset worksheet…
 A dialog box appear , giving name to the new subset worksheet, specify which rows to include
or exclude, mention the rows you want to include or exclude i.e 2,8,23,7.
 Clicking on “ok”, you will get a new worksheet with a name you have given, generally with
a “subset worksheet 1*** ”.
Like…

step 1 step 2

Final Result

2 -How to Merge(combine) worksheets?
 Lets we have two or more than two worksheets with different data, and we
want to combine two of these worksheets into a single worksheet.
 Go to menu ,click on “Data” then click on “Merge worksheets…”
 A dialog box will be appear, click on worksheet that you want to combine
with the current worksheet.
 Click on “OK”.
 You will get a “Merge worksheet”.
Like…

step 1
worksheet 1 worksheet 2

STEP 3

REQUIRED MERGE WORKSHEET

HOW TO GENERATE RANDOM DATA Chi-square?
(Creating random data that follow chi square distribution)
 To generate random data, go to menu , click “Calc” then click “Random
Data”.
 A list of distributions is appear, click on Chi-squre…
 A dialog box will appear, mention the number of rows ( that how many rows of
data you have ta generate?)
 Specify in which column the numbers are to be stored.
 Specify the degree of freedom too.
 Click “OK”, you will get your require random data.
Like…

Confusing points.
 For what we generate random data?
 What is degree of freedom?
 Why we specify degree of freedom?
 If we increase or discrease degree of freedom then what happen to
data?
 Could we perform two sample Z test?
 How cam we distinguist hypothesis testing from variance testing?
 Correlation vs Covariance?
 Test for eaqual variances? How it ca be performed?

REQUIRED RANDOM DATA

How to generate random data-Normal…
(creating random data that follow normal distribution)
 To generate random data- normal, go to menu chose “Calc” then click “Random data”.
 A list of distribution will be appear, click noRmaL…
 A dialog box will appear, mention that in how many rows you generate data
 specify in which column the numbers are to be stored.
 Mention the parameters of normal distribution i.e mean and standard deviation.
 Press “ok”, you will get your required output.
Like…

REQUIRED RESULT

How to generate random data from multivariate normal
distribution?
Multivariate normal distribution . The multivariate normal distribution is an
extension of the univariate normal distribution for applications with a group of variables
that may be correlated.
 To generate random data from multivariate normal distribution, go to menu chose
“Calc” then click “Random data”.
 A list of distribution will be appear, click noRmaL…
 A dialog box will appear, Enter the number of rows of random data you want to
generate , Enter storage column(s) for the generated values, also Enter the variance-
covariance matrix.
 Press “ok”, you will get your required output.
Like…

How to create random data from F-distribution?
 F distribution : The F distribution is a sampling distribution of two independent random variables with chi-square
distributions, each divided by its degrees of freedom . It is most commonly used in test of variance. Use when random
variables are greater than 0.
 To generate random data from data from “F-distribution distribution”, go to menu chose “Calc” then click “Random
data”.
 A list of distribution will be appear, click “F-distribution”.
 A dialog box will appear, specify the dialog box items i.e
Number of rows of data to generate: Enter the number of rows of random data you want to
generate.
Store in column(s): Enter storage column(s) for the generated values.
Numerator degrees of freedom: Enter the number of degrees of freedom for the numerator.
Denominator degrees of freedom: Enter the number of degrees of freedom for the denominator.
Press “ok”, you will get your required output.
Like…

REQUIRED DATA

How to generating random number from t-
distribution?
 t distribution: The t distribution is symmetric about zero but has tails that are more
spread out than those of the normal distribution. With increasing degrees of freedom , the t
distribution looks more like the normal distribution.
 To create random data from t distribution, go to menu chose “Calc” then click Random
data”.
 A list of distribution will be appear, click “t-distribution”.
Number of rows of data to generate: Enter the number of rows of random data
you want to generate.
Degrees of freedom: Enter the number of degrees of freedom you want to define
the t distribution.
 Press “ok”, you will get your required “random data”.
Like…

step 3

REQUIRED DATA
Presented by: Bashir Ul Haq ; +92342 0585558; haq7576@gmail.com

HOW TO CREATING RANDOM DATA FROM
UNIFORM DISTRIBUTION?
 uniform distribution: between two points that you designate. Use to model data that
range over an interval of equally likely values.
 To create random data from t distribution, go to menu chose “Calc” then click Random
data”.
 A list of distribution will be appear, click “UNIFORM…”.
Lower endpoint: Enter a number to define the minimum value for the uniform
distribution.
Upper endpoint: Enter a number to define the maximum value for the uniform
distribution

HOW TO CREATING RANDOM DATA FROM UNIFORM
DISTRIBUTION?
 Bernoulli distribution: Bernoulli distributions are characterized by outcomes with only the
possibility of success (event) or failure (non-event). Data from a Bernoulli distribution have the values of 0
or 1.
 To generating random data from t distribution, go to menu chose “Calc” then click Random data”.
 A list of distribution will be appear, click “Bernoulli…”.
generate.
Event probability: Enter a number between 0 and 1 for the event probability , which will be
used to define the Bernoulli distribution.
Suppose you enter an event probability of 0.2. The new column will contain 1's (for an
event) with a probability of 0.2, and 0's (for a non-event) with a probability of 0.8.

HOW TO CREATING RANDOM DATA FROM BINOMIAL
DISTRIBUTION?
 Binomial distribution : The binomial distribution is based on the probability of observing
successes (events) in a fixed number of independent trials. Data are integers greater than or equal to
0.
 To generating random data from t distribution, go to menu chose “Calc” then click Random data
 A list of distribution will be appear, click “BINOMIAL…”.
Number of rows of data to generate: Enter the number of rows of random
data you want to generate.
Number of trials: Enter the number of trials you want to define the binomial
distribution.
Event probability: Enter a number between 0 and 1 for the event probability ,
which will be used to define the binomial distribution.

HOW TO CREATING RANDOM DATA FROM GEOMETRIC
DISTRIBUTION?
 Geometric distribution: The geometric distribution can model both the number of trials
needed to produce a specified event in a series of independent Bernoulli experiments, or the
number of nonevents that occur before one event occurs in a series of independent Bernoulli
experiments. Generated values are positive integers.
 To create random data from t distribution, go to menu chose “Calc” then click Random data”.
 A list of distribution will be appear, click “GEOMETRIC… ”.
generate.
Event probability: Enter a number between 0 and 1 for the probability that a specified
event occurs.

How to generating random number from
Negative binomial distribution?
 Negative binomial distribution: The negative binomial distribution can model both the number of
observations needed until a specific event occurs a set number of times in a series of independent Bernoulli
experiments, or the number of nonevents that occur before a specific event occurs a set number of times in a series
of independent Bernoulli experiments. Generated values are positive integers.
 To create random data from t distribution, go to menu chose “Calc” then click Random data”.
 A list of distribution will be appear, click “GEOMETRIC… ”.
Number of rows of data to generate: Enter the number of rows of random data you want to generate.
Event probability: Enter a number between 0 and 1 for the probability that a specified event occurs.
Number of events needed: Enter a positive integer representing the number of times the event must occur.
<Options>
Model the total number of trials: Choose to model the total number of trials needed to produce the specified
number of events.
Model only the number of non-even: Choose to model the number of non-events before the specified number
of events occur.

Hypergeometric distribution?
 Hypergeometric distribution :The hypergeometric distribution is used for samples
drawn from relatively small populations, without replacement.
 To create random data from t distribution, go to menu chose “Calc” then click
Random data”.
 A list of distribution will be appear, click “hypergeometric… ”.
Population size (N): Enter the population size, a positive number
Event count in population (M): Enter the number of events in the population,
between 0 and N.
Sample size (n): Enter the sample size, between 0 and N.

How to generating random number from Discrete distribution?
 A discrete distribution is one that you define yourself. For example, suppose you are interested in a distribution made up of three values -1, 0, 1, with probabilities of 0.2,
0.5, and 0.3, respectively. If you enter these values into the worksheet:
Value Prob
-1 0.2
0 0.5
1 0.3
Then you can tell Minitab to use these columns when you are generating
random data or calculating probabilities and probability densities.
Before generating random data, you must put values and their corresponding
probabilities into two columns in the worksheet. Enter those columns in the
Values in and Probabilities in boxes
 Random data”.
 A list of distribution will be appear, click “Discrete… ”.
 dialog box will appear, specify the dialog box items i.e
Number of rows of data to generate: Enter the number of rows of random data you want to generate.
Values in: Enter the column containing the values you want to be included in the distribution.
Probabilities in: Enter the column containing the probabilities that correspond to the discrete numbers in the Values in box.

Integer distribution?
 Integer distribution: which is a discrete uniform distribution that ranges from the
minimum to the maximum integer value specified. Each integer in the range has
equal probability.
Random data”.
 A list of distribution will be appear, click “integer…”.
Minimum value: Enter the beginning integer.
Maximum value: Enter the ending integer.

Piosson distribution?
 Poisson distribution: The Poisson distribution is often used when the
probability of an event is small.
 To create random data from “Poisson distribution”, go to menu chose “Calc”
then click Random data”.
 A list of distribution will be appear, click “poisson…”.
Mean: Enter a mean value greater than 0 and less than or equal to 709, which
will define the Poisson distribution.

Cauchy distribution?
 Generates random data from a Cauchy distribution . The Cauchy distribution is symmetric
around zero, but the tails approach zero less quickly than do those of the normal distribution.
 To create random data from “Poisson distribution”, go to menu chose “Calc” then click
Random data”.
 A list of distribution will be appear, click “cauchhy…”.
Location: Enter a number for the location you want to define the Cauchy
distribution.
Scale: Enter a number for the scale you want to define the Cauchy
distribution

exponential distribution?
 Generates random data from an exponential distribution . Use the exponential
distribution for time series data when the data are constant, such as when units
have a constant failure rate. Use when random variables are greater than 0
 To create random data from “cauchy distribution”, go to menu chose “Calc” then
click Random data”.
 A list of distribution will be appear, click “cauchhy…”.
Number of rows of data to generate: Enter the number of rows of random data to
generate.
Scale: Enter a scale value to define the exponential distribution. The scale
parameter equals the mean, when the threshold parameter equals 0.
Threshold: Enter a threshold to define the exponential distribution.

Gama distribution?
 Generates random data from a gamma distribution . The gamma distribution is often used to model positively
skewed data. Use when random variables are greater than 0
 To create random data from “gama distribution”, go to menu chose “Calc” then click Random data”.
 A list of distribution will be appear, click “gama…”.
Number of rows of data to generate: Indicate the number of rows of random data
to generate.
Shape parameter: Enter a shape parameter to define the gamma distribution.
Scale parameter: Enter a scale parameter to define the gamma distribution.
Threshold parameter: Enter a threshold parameter to define the gamma
distribution
Press “ok”, you will get your required “random data”.

How to find “Descriptive Statistics” from
basic statistics?
 BASIC STATISTICS: welcome to this course on basic statistics. ... statistics help us in converting data
into information which helps us in making decisions.
 Descriptivee statistics: The branch of statistics which deal with summarization and description of
numerical facts is called descriptive statistics
Summarization: DATA COLLECTION, CLASSIFICATION, TABULATION AND
GRAPHS etc.
Description: To describe data in meaningful way by finding averages,
dispersion, skewness and kurtosis.
 Being by typing or importing .the data into main worksheet .
 Click Stat, Basic Statistics, and descriptive Statistics...
 Select the Variable or Variables you wish to describe.
 Press Ok, you will get the output in the session window.
LIKE…

How to perform Correlation?
 Correlation :A correlation coefficient measures the extent to which two
variables tend to change together. Minitab offers two different correlation
analyses:
 Steps for performing Correlation
 Type the data into two columns.
 Click Stat, Basic Statistics, and Correlatiion …
 Transfer the variables into variables: box GMAT, GPA
 Choose Pearson Correlation Method.
 Click OK, you will have the output in the session window.
LIKE…

How to perform Covariance?
 COVARIANCE: the covariance is a measure of the relationship between two variables. However, the
covariance has not been standardized, as is done with the correlation coefficient. The correlation
coefficient is standardized by dividing by the standard deviation of both variables.
 STEPS TO PERFORMING CCOVARIANCE
 Type the data into two columns.
 Click Stat, Basic Statistics, and Covariance…
 Specify thee names of the variable. GMAT, GPA
 Select Pearson Method.
 Click OK, you will have the output in the session window.
 LIIKE…

How to perform Normality test?
 Normality test: Determine whether your data follow a normal distribution, use
when you have continuous measurements Such a length or weight.
 Steps to performing Normality test:
 Type or import the data into main worksheet ( worksheet 1)
 Click Stat, Basic Statistics and Normality test…
 Transfer the variable into variable box.
 Choose a method from tests for normality… Kolmagorovve
 Press OK, you will get output in session window.
LIKE…

confussion

How to perform Outlier test?
 OUTLIER: Outliers are data values that differ greatly from the majority of a set of
data
Use to identify a single outlier in a sample. The hypotheses are as follows:
· H0 (the null hypothesis): All values in the sample are from the same,
normally distributed population.
· H1 (the alternative hypothesis): One of the values in the sample is not from
the same, normally distributed population
 Steps for detecting Outlier
 Type or import data.
 Click Stat, Basic Statistics and Outlier…
 A dialog box is appear, shift the variable into variable:box
 Click Ok, you will get output in session window.
Like…

How to perform “Descriptive statistics”?
 Descriptivee statistics: The branch of statistics which deal with summarization and description of
numerical facts is called descriptive statistics
Summarization: DATA COLLECTION, CLASSIFICATION, TABULATION AND
GRAPHS etc.
Description: To describe data in meaningful way by finding averages,
dispersion, skewness and kurtosis.
Being typing or importing data into main worksheet.
Click “Stat” a list is appear, then click on “Basic statistics”.
Another list of commands will appear, select “Display descriptive statistics…”
A dialog box is appear, shift the one variabe into variables and other variables:box to
By variables:box.
Press oK, you will get output in the session window.
LIKE…

How to perform “1-sample Z test”?
 1-Sample Z: Use 1-Sample Z to compute a confidence interval or perform a hypothesis test
of the mean when s is known. For a two-tailed one-sample Z-test, the hypotheses are:
H0 : m = m 0 versus H1: m ≠ m 0 where m is the population mean and m 0 is
the hypothesized population mean.
 Type or import the data into one column.
 Click Stat , Basic Statistics , and 1-Sample Z…
 Type or Select the variable name i.e C1, C2,C3 etc
 Type or input the value of the population standard deviation ( Sigma ) i.e 76.
 Type the value Teat mean under the null hyypottheesis
 Click Options… Type or specify the value for Confidense interval i.e 95.0
 In the Alternative box select not equal.
 Click Ok, you will get output in session window.
LIKE…

How to perform “1-sample t- test”?
 1-sample T: Use 1-Sample t to compute a confidence interval and perform a hypothesis test of the
mean when the population standard deviation, s, is unknown. For a two-tailed one-sample t,
H0: m = m 0 versus H1: m ≠ m 0
where m is the population mean and m 0 is the hypothesized population
mean.
 Type or import the data into one column.
 Click Stat , Basic Statistics , and 1-Sample t…
 Type or Select the variable name i.e C1, C2,C3 etc
 Use the “sample deviation” ( 7.66) and specify the “Test mean” under the Null hypothesis (550).
 Click Option… and specify the Alternative hypothesis ( greater than).
 Click Ok, you will have the following output inn main worksheet.

How to perform Two- sample t…?
 Two-sample t:Use 2-Sample t to perform a hypothesis test and compute a confidence
interval of the difference between two population means when the population standard
deviations , s's, are unknown. For a two-tailed 2-sample t
H0: m 1 - m 2 = d 0 versus H1: m 1 - m 2 ≠ d 0 where m 1 and m 2 are the
population means and d 0 is the hypothesized difference between the two
population means.
 Type or import the data into two columns.
 Click Stat , Basic Statistics , and 2-Sample t…
 Shift the variables into sample 1 and sample 2.
 Click Options… and specify the hypothesized difference ( test mean ) i.e 0.
 Type the value of Confidence interval i.e 95.0
 Indicate that the Population variances are not equal
 Click Ok, you will get the following result.

How to perform “paired sample t…”?
 Paired sample t…: This is appropriate for testing the mean difference between paired observations
when the paired differences follow a normal distribution.
 Type or import the data.
 Click Stat, Basic statistics and paired t…
 Select the variable name of the First sample. C1
 Select the variable name of the Second sample. C2
 Click Options…
 Specify TEST MEAN and Type the Hypothesized Paired difference. 0
 Specify the Alternative, Click Ok. Greater than
 Press Ok, The following output will be appear.

How to perform “one-sample proportion”.
 A proportion refers to the fraction of the total that possesses a certain attribute. For example,
suppose we have a sample of four pets - a bird, a fish, a dog, and a cat. ... Therefore, the
proportion of pets with four legs is 2/4 or 0.50.
 Click Stat, Basic Statistics and 1 Proportion…
 Shift the variable into box,Click Summarized data and type the sample size (Trials) and the
values of “x” (Successes) i.e 1499 398.
 Click “Options..., Type the value of the Confidence Level.
 Chose “perform hypothesis test” then specify hypothesized proportion i.e 0.56
 Specify the Alternative as not equal, Click OK,
 Click Ok. You will get output in session window
LIKE…

 INTERPRETATION
WE SEE THAT THE VALUE OF SAMPLE PROPORTION (SAMPLE P) =0.079365 AND
THE P VALUE IS 0.00, SO THERE IS ENOUGH EVIDENCE TO INFER THAT WE NEED TO
FOLLOW THE ALTERNATIVE HYPOTHESIS i.e p HH 0.56.

How to perform “2 sample proportion”?
 Click Stat, Basic Statistics and 2 Proportions…
 Specify the variables to be tested C1, C2 in other words
 Specify samples in different columns.
 Click Summarized data and type the sample sizes (Trials) and the values of “x1” and “x2” (Successes)
i.e 1499 398, 1544 433
 Click “Options..., Type the value of the Confidence Level. 0.95
 Specify the Alternative as not equal, Click OK,
 Click Ok. You will get output in session window
LIKE…

How to generate “Fitted line plot”?
 Fitted line plot: The "fitted line plot" command is one way of obtaining the estimated regression
function between a response y and a predictor x. The "fitted line plot" command provides not
only the estimated regression function, but also a scatter plot of the data adorned with the
estimated regression function.
 Type or import the data. Open file Xm13-01
 Click Stat, Basic Statistics, and Regression…
 Select “Fitted line plot” a dialog box is appear, shift the independent variable to Predictor(X)
and dependent variable to Response (Y) . Quality or C1, Profit or C2.
 Chose the type of regression model Linear
 Press ok, you will have the required output in session window.
 LIKE…

How to perform Orthogonal Regression?
 Type or import data .
 Go to “Menu”, Click on “Stat” a list will appear click on “regression…” .
 Another list of Command is appear , Click on “Orthogonal Regression”.
 A dialog box appears, mention the predictor variable and response variable
 Specify “Error variance ratio ( Y/X)”.
 Click “OK”, in each table.
 The out put will appear in session window.
LIKE…

How to perform One way ANOVA?
 One way ANOVA:The One-Way ANOVA ("analysis of variance") compares the means of two or more
independent groups in order to determine whether there is statistical evidence that the associated
population means are significantly different. One-Way ANOVA is a parametric test.
 Type Or import data into Worksheet 1. Open file Xm15-01
 Go to menu , click Stat, ANOVA and then One way…
 Type the variable name of the response variable and the name of the factor variable
i.e Quality, Price or C1,C2
 Click Comparissions…, Select Turkey’s method and specify the significance level i.e o.o5
 Press OK, You will get the following result in session window.

How to perform “Balance ANOVA”?
 Balance ANOVA: Determine whether the means of two or more groups differ,
when the data are balanced.
 TO performe “Balance ANOVA” the following steps must be performed.
 Type or import data with variables “X” and “Y” into worksheet.
 Go to menu, Click Stat, ANOVA and Balance ANOVA.
 A dialog box appears, transfer “Y” variable to “Responsees” and “X” variable
to “Model”.
 Press ok, the output requested will appear in the session window.
Like…

 Interpretation:
we see, the value of the test statistic is F=0.04 and p=
o.45,which means there is evidence to infer that all the
means are equal.

How to read Matrix?
 To read Matrix in minitab the following steps must be performed:
 First go to menu bar, click on “Editor” a list of commands will appear.
 Click on “ Enable command…
 Click on “Calc”, a list of commands will appear, click on “Matrix…”.
 Another list of command will appear, click on read matrix…,
 A dialog box appears, Specify the dialog box items:
Number of rows
Number of columns
Read into matrix.
 Click Ok, then put data in session window, according to the rows and colums you have mentioned, then click
enter.
 To view the contents of a matrix, click on “Data” , Display data, shift M1 to box.
 Press Ok. The requested output will appear in the session window.
Like…

IF WEALTH IS LOST
NOTHING IS LOST
IF HEALTH IS LOST
SOMETHING IS LOST
IF BEHAVIOUR IS GONE
EVERYTHING IS GONE !

"A BASIC GUIDE TO MINITAB" published by Bashir Ul Haq

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