To know more about Normality Test, you can explore Simplilearn’s Minitab with Statistics Training. 05, we can assume the “Before” data is normal. Here we can notice that since the P value is greater than. Once we click ok, Minitab generates the probability plot in a separate window. While there are multiple kinds of normality tests available, the Anderson Darling Test is the most reliable and commonly used test. Now we click on Anderson-Darling and then click on OK. Double click on before in the left hand side box to select it. In this example, let us test the Column which has before, data for normality. Click on Normality Test then enter the variables on the respective columns. Go to Start menu and then move to Basic Statistics. Go to File Menu, click Open Project and then load the file including Cholesterol levels at fasting. Example of conducting a Normality Test Taking the example of Cholesterol levels at fasting, before breakfast and after breakfast levels, let’s conduct a normality test. After clicking OK, Minitab generates the probability plot in a separate window. Step 3: Click on Normality Test and then enter the variables on the respective columns. Step 2: Go to Start menu and then move to Basic Statistics. Step 1: Go to File menu, click Open Project and then load the data to be analyzed. Let’s have a look at the steps to perform a normality test using Minitab.
Minitab has statistical tools that allow one to perform statistical calculations with ease. One can conduct a Normality test using Minitab. Many statistical analyses require that the data come from normally distributed populations. The normal distribution is the most common statistical distribution because approximate normality arises naturally in many physical, biological, and social measurement situations. A normal distribution is a bell-shaped curve that is symmetric about its mean. Normality Test helps one to determine whether a data is following a normal distribution or not. Normality is one of the major concepts in statistics used for various statistical calculations.
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