If we reject the null, we accept the alternative.
In statistical terms, we talk in terms of accepting or rejecting the null hypothesis. Alternative hypothesis (Ha): The data is not normal.Null hypothesis (Ho): The data is normal.The two hypotheses for the Chi-Squared Goodness-of-Fit test are: That means you are testing the data with regard to a null hypothesis and an alternative hypothesis. The Chi-Squared Goodness-of-Fit test is actually a hypothesis test. If you don’t remember what the sample size was, you can refer to the count listed in the descriptive statistics. The sample size is the number of items in the data set, which was 50 for this example. The information provided are slightly similar to information in Minitab Graphical Summaryįor the Chi-Squared Goodness-of-Fit test, you will need to note the sample size (or count), the same standard deviation, and the sample mean. Excel returns descriptive summary statistics for your data set in Sheet 3.If you check these extra boxes, Excel will simply provide you with additional information that we won’t be using at this time. You can also check the Confidence level for mean and the Kth largest and smallest boxes, though that information isn’t required in the Chi-Squared Goodness-of-Fit test, which is the test we are running to test for normality of the data.
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Most us are relying to our advance statistical software such as Minitab, SigmaXL, JMP and many more to validate the data normality. However, deeper analysis is require to validate the normality of the data since it is affecting our analysis method.
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In our previous post, we have discussed what is normal distribution and how to visually identify the normal distribution.