04.Graphic Capabilities

Lesson 4 Graph Capabilities

Agenda

Pareto Chart Histogram Normality Test Marginal Plot Box Plot Scatter Plot Matrix Plot

Business Scenarios

The graphical tools of Minitab are used across organizations to understand and interpret data for taking key business decisions. Some examples that are used in the following slides include:

• Analyze defects data to identify areas where most defects are originating from. This is also called distinguishing “vital few" from the "trivial many” so that you can focus your emphasis on resolving the vital few.

• Analyze the shape and spread of data to understand how large is the variation in the data.

• Conduct Normality tests to identify whether the data distribution is Normal or Non Normal

• Assess relationship between two or more variables to see if one can impact another

PARETO GRAPH Graphs

A Pareto Chart is used to determine which of the defects comprise the "vital few" and which are the "trivial many”. Let’s generate a Pareto Chart from an existing set of data. 1. Go to File> Open Project 2. Load an existing file to load the set of data. In this example we are loading Pareto.mpj.

Steps to create a Pareto Chart

To generate Pareto Chart go to Stat > Quality Tools> Pareto Charts


Fill out the fields as follows: •Defects or Attribute data are all types of errors that are identified in the given data this example we will select “Category” for Defects. •Frequencies are the number of defects according to category in the given data. In this example we will select “Quantity”. •Click Ok to generate the chart.


Tip 1 – To select a column for a particular field, place the cursor in the field and then double click the column name as it appears in the left side of the dialog box.

Tips

Tip 2 – You can add Title to the Chart and labels to the x and y axis by using the Options…

Minitab generates the Pareto Chart. This can be copied into PowerPoint or saved as a graphic file for future use. Note that 80% of the defects lie in the category of G, F and partly in E. This makes it easier for us to focus our efforts towards resolving few problem areas rather than focusing on a large set of categories.


Save the Graph for future use

Go to File > Save Graph As… to save the graph as a file for future use.

HISTOGRAM Graphs

Histogram is used to examine the shape and spread of sample data. Let’s generate a Histogram from an existing set of data. •Go to File > Open Project… •Load the file. In this example we use GPA.mpj to analyze the Grades of students. •Now let’s generate the Histogram of the GPA results.

Steps to create a Histogram

Once the data is loaded, generate the Histogram by Graph > Histogram


The most commonly used Histogram type is “With Fit.” This type of Histogram is used to evaluate how well the sample data follows a specific distribution. •Click on “With Fit” to select the type of histogram you want to create. •Then click OK.


Fill out the next screen as follows: •We will select GPA as our X value for our Graph Variables. Double click on GPA to select. • Click OK


Minitab now completes our histogram for us ready to be copied and pasted into your PowerPoint presentation or save for later use. This data does not look like it is very normal. We can use Minitab to test this distribution for normality.


NORMALITY TEST Graphs - Histogram

•Normality Test is conducted to test if the data in the distribution is Normal. •Data is considered Normal if the P value of the data is >= 0.05. •Let’s test the normality of the GPA data as used for creating Histograms. To start go to: •Stat > Basic Statistics > Graphical Summary

Steps to conduct Normality Test in Histogram

Fill out the screen as follows: •Double Click GPA to select it as the variable for Normality Test. •Click Ok Tip: Use “By variables” to create separate graphical summaries for each level of a grouping variable. The “Confidence Level” indicates the level of confidence to which the normality of data will be calculated.


Note that now we not only have our Histogram but a number of other descriptive statistics as well. Also note that P value of our data is .038 which is less than 0.05. So, we conclude with 95% confidence that the data is not normal.


MARGINAL PLOT Graphs - Histogram

Steps to create Marginal Plots

Marginal plots are used to assess the relationship between two variables and examine their distributions. A marginal plot is like a scatter plot built along with Histograms , Boxplots , or Dotplots in the margins of the x- and y-axes. Load the MPJ file by File > Open project . The below file includes data for tests conducted on 6 types of bottle heads across two shifts to see how much quantity of Filler was being entered.

To generate a Marginal Plot go to: •Graph > Marginal Plot…


You can create Marginal Plots using Histograms, Box Plots or Dot plots. Please select the one you want to create. •In this example we are creating a Marginal Plot with Histogram. •Click on Ok


Fill out the screen as follows: •Select filler 1 for the Y variable. •Select head for the X Variable •Select OK. This will help us analyze the relationship between kind of head and the amount of Filler. Tip: You can select more options on the graph and its axes by using the buttons below.


Note that now we not only have our Histogram but a dot plot of each head data as well. Note that head number 1 seems to be the source of the highest reading. This means that Head 1 is allowing more Filler to be entered into the bottles.


BOX PLOTS Graphs

Box plot is used to assess and compare sample distributions. Box plots are useful to identify the range of the distribution and the outliers in the data. Let’s use the same data to create a Box plot.

Steps to create Box Plots

You can create different types of Box plots – with or without groups or with multiple Y axes. In this example we will create the Simple Box Plot graph. Select the graph and click Ok.


Select the field on which you need to generate the Box plot. We have taken Filler 1 as the field for generating Box Plots. Tip: You can customize your Box Plot by using the various buttons available in this dialog box.


The Box Plot is generated. The center line in the box is the Median of the data. Half the points are above and half of them are below the median. The upper whisker indicates the upper most point in the data and the lower whisker indicates the lowest point. Any outliers are represented by * in the graph


Median

Upper Whisker

Lower Whisker

Group Box Plots represent more than one type of data in the Box Plots. To create group Box Plot, select the With Groups Box Plot option and Click OK.

Steps to create Group Box Plots

Fill out the screen as follows: •Select “filler 1” for our Y variable. •Select “head” for our X Variable. •Click OK.

Steps to create Group Box Plots .

Note that now we have a box plot broken out by each of the various heads. Note that head number 1 again seems to be the source of the high readings.

Steps to create Group Box Plots

SCATTER PLOTS Graphs

A scatter plot is used to illustrate the relationship between two variables by plotting one against the other We will use the Grade Point average scores of students as an example to generate Scatter Plot. •Go to File>Open Project. •Load the GPA.mpj.

Steps to create Scatter Plots

Go to Graph > Scatter Plot...


•Scatter Plots can be made with multiple combinations of lines, connects and groups. •Let us start with creating a Simple scatter plot. •Select Simple and then click OK.


Fill out the screen as follows: •Select GPA for Y Variable. •Select Math and Verbal for our X Variables. •Click Ok.


We now have two Scatter plots of the data stacked on top of each other. We can display this better by tiling the graphs.


To see multiple graphs as Tiles go to Window > Tile


Now we can see both Scatter plots of the data as Tiles. You can see that there seems to be a positive relationship between score in Maths and GPA and the scores in Verbal and GPA. As the scores in each of these increases, the overall GPA also increases.


MATRIX PLOTS Graphs

Matrix Plot helps to assess the relationships between many pairs of variables at once by creating an array of scatter plots. To create Matrix Plots go to Graph > Matrix Plot. We will create Matrix plot using the same set of GPA data.

Steps to create Matrix Plot

Let us create a Matrix Plot with Groups. Select the type of graph and click OK.


Fill out the fields as follows: •Click in the “Graph variables” block •Highlight all three available data sets •Click on the “Select” button. •Click OK.


We now have a series of Scatter plots, each one corresponding to a combination of the data sets available. Note that there appears to be a strong correlation between Verbal and GPA data.


Summary

In this session we learnt about common business scenarios where Minitab is extensively used. These include:

Analyze defects data to identify areas where most defects are originating from. This is also called distinguishing “vital few" from the "trivial many” so that you can focus your emphasis on resolving the vital few.

Analyze the shape and spread of data to understand how large the variation in the data is. Conduct Normality tests to identify whether the data distribution is Normal or Non Normal Assess relationship between two or more variables to see if one can impact another We learnt about important graphs like Pareto Chart Histogram Normality Test Marginal Plot Box Plot Scatter Plot, and Matrix Plot We also learnt how these graphs are created in Minitab and how these can help in business

scenarios. In the next session we will cover statistical capabilities of Minitab.

1. In the Pareto chart defects or attribute data field defines a) Types or categories of defects in the data b) no of times data is present c) both a & b d) none of the above

Test Questions

Answer: a) Types or categories of defects in the data

2. In the normality test data is considered not normal if the p value is a) equal to 0.05 b) less than 0.05 c) greater than 0.05 d) none

Test Questions

Answer: b) less than 0.05

3. Matrix plot is used to a) illustrate the relationship between two variables b) assess the relationships between many pairs of variables c) assess the relationship between two variables and examine their distributions d) all the above

Test Questions

Answer: b) assess the relationship between many pairs of variables

4. Which menu convention we are using for hypothesis tests in Minitab? a) File menu b) Stat menu c) Tool menu d) Edit menu e) None

Test Questions

Answer: b) Stat menu

5. Which menu convention is used to arrange the windows as a cascade, tiles or minimized form? a) window menu b) tool menu c) help menu d) assistant menu e) all the above

Test Questions

Answer: a) window menu

6. Scatter Plots can be made with a) Multiple groups b) Multiple lines c) Multiple combinations of lines, connects and groups. d) None

Test Questions

Answer: c) Multiple combinations of lines, connects and groups

7. In the Box Plot the center line in the box defines a) median of the data b) upper most point c) lowest Point d) none

Test Questions

Answer: a) Median of the data

End Of Session - 4

04.Graphic Capabilities

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