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A low p-value (e.g.

As such, a student scoring just 2 on the scale "could" be considered an outlier. See complete feature list. Enjoy our full support When you purchase Minitab, you get a host of additional benefits from a company that understands your data analysis challenges and quality improvement goals.

What’s a Pareto Chart?

A Pareto Chart is a quality chart of discrete data that helps identify the most significant types of defect occurrences. It does this by It does this by skip to Main Content.

However, it is not a difficult task, and Minitab provides all the tools you need to do this. In the section, Test Procedure in Minitab , we illustrate the Minitab procedure required to perform linear regression assuming that no assumptions have been violated. First, we set out the example we use to explain the linear regression procedure in Minitab. An educator wants to determine whether students' exam scores were related to revision time. For example, as students spent more time revising, did their exam score also increase a positive relationship ; or did the opposite happen?

The educator also wanted to know the proportion of exam score that revision time could explain, as well as being able to predict the exam score. The educator could then determine whether, for example, students that spent just 10 hours revising could still pass their exam.

Therefore, the dependent variable was "exam score", measured on a scale from 0 to , and the independent variable was "revision time", measured in hours. To carry out the analysis, the researcher recruited 40 students. The length of time revising i. Expressed in variable terms, the researcher wanted to regress Exam score on Revision time.

A linear regression was used to determine whether there was a statistically significant relationship between exam score and revision time. The example and data used for this guide are fictitious. We have just created them for the purposes of this guide. In Minitab, we entered our two variables into the first two columns and.

Under column we entered the name of the dependent variable, Exam score , as follows: Then, under column we entered the name of the independent variable, Revision time , as follows: Finally, we entered the scores for the dependent variable, Exam score , into the column, and independent variable, Revision time , into the column. This is illustrated below:. It does not matter whether you enter the dependent variable or independent variable under C1 or C2.

We have just entered the data into Minitab this way in our example. In this section, we show you how to analyze your data using a linear regression in Minitab when the seven assumptions set out in the Assumptions section have not been violated.

Therefore, the three steps required to run a linear regression in Minitab are shown below:. You will end up with the dialogue box shown below:. To transfer the two variables, you first need to click inside the Response: This will activate the button it is usually faded: You now need to follow the same procedure, but for the independent variable, which should be transferred into the Predictors: The output that Minitab produces is shown below.

Adjusted R 2 is also an estimate of the effect size, which at This indicates that, overall, the model applied can statistically significantly predict the dependent variable, Exam score. In addition to the linear regression output above, you will also have to interpret a the scatterplots you used to check if there was a linear relationship between your two variables i.

Remember that if your data failed any of these assumptions, the output that you get from the linear regression procedure i. When you report the output of your linear regression, it is good practice to include: An introduction to the analysis you carried out.

Information about your sample, including any missing values. A statement of whether there was a statistically significant relationship between the dependent and independent variable, including the observed F -value F , degrees of freedom DF and significance level, or more specifically, the 2-tailed p -value P.

The regression equation for your model. Based on the Minitab output above , we could report the results of this study as follows:. The regression equation was: In addition to reporting the results as above, a diagram can be used to visually present your results. For example, you could use a scatterplot with confidence and prediction intervals although it is not very common to add the last. This can make it easier for others to understand your results.

Furthermore, you can use your linear regression equation to make predictions about the value of the dependent variable based on different values of the independent variable. Whilst Minitab does not produce these values as part of the linear regression procedure above, there is a procedure in Minitab that you can use to do so. Linear regression using Minitab Introduction Linear regression, also known as simple linear regression or bivariate linear regression, is used when we want to predict the value of a dependent variable based on the value of an independent variable.

Minitab Assumptions Linear regression has seven assumptions. Assumptions 1 and 2 are explained below: Your dependent variable should be measured at the continuous level i. If you are unsure whether your dependent variable is continuous i. Your independent variable should be measured at the continuous or categorical level.

No package is more accurate, reliable, or easy to use. A powerful new graphics engine that delivers engaging results that offer tremendous insight into your data An effortless method to create, edit, and update graphs The ability to customize your menus and toolbars so you can conveniently access the methods you use most.

Interactively recreate custom graphs with new data Easily place multiple graphs on one page Automatically update graphs as data change Brush graphs to explore points of interest Export: Run chart Pareto chart Cause-and-effect diagram Variables control charts: Random number generator Density, cumulative distribution, and inverse cumulative distribution functions Random sampling Macros and Customization. Click on below button to start Minitab 18 Free Download.

This is complete offline installer and standalone setup for Minitab This would be compatible with both 32 bit and 64 bit windows. Beatskillz Soultastik KZ v1. June 16, 0. Please complete the required fields.

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