# HOW TO USE MINITAB: INTRODUCTION AND BASICS. Noelle M. Richard 08/27/14

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1 HOW TO USE MINITAB: INTRODUCTION AND BASICS 1 Noelle M. Richard 08/27/14

2 CONTENTS * Click on the links to jump to that page in the presentation. * 1. Minitab Environment 2. Uploading Data to Minitab/Saving Projects 3. Graphical Summary ( First Look ) 4. Normality Test (Is your data normally distributed?) 5. Descriptive Statistics (Mean, Variance, Range, etc.) 6. Confidence Intervals and Plots (Estimates of the mean) 7. ANOVA tables (Analysis of Variance) 8. Hypothesis Tests (Are two sample means significantly different? Or are they equivalent?) 9. One-Way ANOVA (Comparing 3 or more sample means) 10. Tukey Comparisons (Comparing 12+ sample means) 11. Standardizing Data 2

3 WHAT IS MINITAB? * For more Minitab tutorials, click the links below. * A program used for statistical analysis As of June 2014, version 16 Can be used for: Basic Statistics Graphs/Summary Statistics Confidence Intervals Hypothesis Tests ANOVA Tables Regression Analysis and Modeling Simple Regression General Linear Models 3

4 WHAT IS MINITAB? Quality Control Control Charts Capability Analysis Gauge R & R Studies Design of Experiments Randomized Complete Block Designs Factorial Designs Fractional Factorial Designs Split-Plot Designs Response Surface Unfamiliar with these terms? No worries! They will be explained later on. 4

5 MINITAB ENVIRONMENT Project Window Where you enter in your data Session Window Where your results/output will be displayed Toolbar/Dropdown Menus 5

6 MINITAB ENVIRONMENT 6

7 PROJECT WINDOW Minitab analyses data in columns If data arranged in rows, transpose in excel first Transposing in Minitab may mess up your data First Row (C1, C2, C3, etc.) Column Labels D = Date T = Text Blank = Numeric Second Row Variable Names 7

8 GETTING DATA INTO MINITAB 1. Type in yourself 2. Copy/Paste from Excel Highlight/copy cells in Excel Highlight exact # of cells in Minitab Project Window (MUST be exact dimensions) Paste 3. Import FileOpen Worksheet Select the Excel file and Open This will import all worksheets from the file. Close out any you don t want. 8

9 IMPORTING DATA FROM EXCEL 9

10 SAVING PROJECT Saving your Project will: Save all data entered into Project Window(s) All output in the Session Window Can also save individual worksheets to open in other projects 10

11 GRAPHICAL SUMMARY Data in the following examples: There are rectangle pieces with die on each. The die have different diameter sizes. We are measuring the width of a porous material surrounding each die. Pieces were etched using different methods. Great first look at your data Add the variable(s) you want to look at in Variables box Can also split data up using By variables Will produce separate graphs of Variable for each By Variable 11

12 GRAPHICAL SUMMARY/NORMALITY Output: Summary Statistics, Histogram, Test for Normality, etc. Normality Test: P-Value 0.05 Data not normally distributed Why is this important? Many statistical techniques assume normality of your data Anderson-Darling Test only good for larger samples (n > 20) If n < 20, see next slide. 12

13 NORMALITY TEST USING PROBABILITY PLOT Use if sample size < 20 Output If the data are normally distributed, most red data points should lie on the center blue line. Almost all points should be within the outer blue lines. 13 The plot to the left shows data that is NOT normally distributed.

14 DESCRIPTIVE STATISTICS Shows various summary statistics like mean, variance, range, etc. Can select what statistics you want to see 14

15 DESCRIPTIVE STATISTICS Output stored in Session Window Can Highlight and Copy all text 15

16 CONFIDENCE INTERVALS/INTERVAL PLOTS 95% confidence intervals (C.I.) for mean Your data is a sample from a large population Use C.I. to estimate the true mean for the population 95% = confidence level Graphical Summary produces C.I. for mean, median and standard deviation Can change confidence level to what you want Higher level means wider interval. Usually 95% is sufficient Smaller sample sizes and larger std. deviation produce wider intervals Can draw interval plot to visualize the intervals 16 **

17 CONFIDENCE INTERVALS/INTERVAL PLOTS Can find intervals (for the mean) of specific group(s) in your data Output: 17

18 ANOVA TABLES Analysis of Variance How much of your variation is within groups? How much of your variation is between groups? Are the means of 2 or more samples statistically equivalent? ANOVA tables can answer these questions. They are used in various other areas of statistics too Seeing how well a regression model fits data Finding Repeatability and Reproducibility in Gage R & R Studies One-Way ANOVA tables are used to compare the means of more than 2 samples. In order to proceed with One-Way ANOVA, we need to understand Hypothesis Tests. 18

19 HYPOTHESIS TESTS Answer questions like: Are population means equivalent? Is one greater than the other? Do populations have the same std. deviation? Each test contains two hypotheses: 1. Null Hypothesis: This is the default hypothesis. Usually, it assumes there is no relationship between 2 phenomena ex.) 2 population means are equivalent. 2. Alternative Hypothesis: Another hypothesis that could be true ex.) mean 1 is larger than mean 2 The goal is to either: 1. Not Reject the null hypothesis or 2. Reject the null hypothesis, in favor of the alternative 19

20 HYPOTHESIS TESTS After the hypotheses have been stated, the test quantifies the evidence against the null hypothesis. This evidence is reflected in a value known as the test statistic. From this test statistic, we get a p-value, which is used determine whether to reject the null hypothesis or not. Large p-value large amount of evidence in favor of the null hypothesis Small p-value small amount of evidence in favor of the null hypothesis Rule of Thumb: p-value 0.05 do not reject the null hypothesis p-value < 0.5 reject the null hypothesis in favor of the alternative Click here for more information about p-values, if interested. 20

21 ONE-WAY ANOVA As mentioned before, it is used to compare the means of more than 2 samples. How does it work? It s a Hypothesis Test! Null Hypothesis: the samples were drawn from populations with the same mean values. Alternative Hypothesis: the samples were drawn from pops with different mean values. Note: In this case, if you reject the null hypothesis, you ONLY know that at least one of the samples is different than the others. But you do not know which one it is. Can use confidence intervals to estimate the difference between population means. Intervals that do not contain 0 indicate the means are significantly different. 21

22 ONE-WAY ANOVA / HYPOTHESIS TESTS Can use Minitab Assistant (v.16 only) Select what type of test you want to do. Here, we will proceed with One-Way ANOVA in the 3 rd column. Remember, this is for comparing means of more than 2 samples. If you are comparing only two samples, use the 2-Sample t test. Data from your samples should be in separate columns. 22

23 ONE-WAY ANOVA / HYPOTHESIS TESTS * This process in Minitab only works for 12 samples or less. * Use Tukey method if you have more than 12 Choose how your data is set up Several windows will now pop up with your results, as well as some interpretation. 23

24 ASSISTANT OUTPUT Also provides confidence intervals for the means 24

25 TUKEY COMPARISONS Are means of samples/groups significantly different? Use Tukey s Method Pair-wise comparisons of means Calculates confidence intervals for Mean 1 Mean 2, for all pairs. If the confidence interval contains 0, no significant difference b/w the two means. Then, using these intervals, can group means. Means in same group are not significantly different. What s special about Tukey s method? Considers all comparisons simultaneously. Confidence levels of the individual intervals are adjusted in order to reduce error. Use if you have more than 12 groups whose means you want to compare. 25

26 MINITAB- TUKEY Output Groupings based on Tukey 26

27 STANDARDIZING DATA Sometimes, standardizing data is useful. Can be easier to work with the data Standardizing: For each data point, subtract off the mean, divide by standard deviation Store your results in the next empty column in your dataset 27

28 REFERENCES Khan, R. M. (2013). Problem solving and data analysis using minitab: A clear and easy guide to six sigma methodology (1st ed.). West Sussex, United Kingdom: Wiley

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