For example, test scores of college students follow a normal distribution. You should save the data file ^Class Data to your computer. Test the null hypothesis that the sample data in the input vector x comes from a normal distribution with parameters µ and σ equal to the mean (mean) and standard deviation (std) of the sample data, respectively. If the p-value is equal to or less than alpha, there is evidence that the data does not follow a normal distribution. This approximation is termed the normal distribution approximation, Gaussian approximation, or Silverman's (1986) rule of thumb.

Use the probability distribution function normcdf as a function handle in the chi-square goodness-of-fit test (chi2gof). A resource for JMP software users. Altough your data is known to follow normal distribution, it is possible that your data does not look normal when plotted, because there are too few samples. It would be great if the software could provide distribution identification analyses in a manner similar to those of JMP (the exploratory software package associated with SAS). How to Create a Histogram in JMP Step One: Download the data.

The p-value for the lognormal distribution is 0.058 while the p-value for the Weibull distribution is 0.162. Using Dataset 1 in file Sampledata.xlsx, test flow data at Station 1 (Q_1) for conformance with a normal distribution and, if the data do not follow a normal distribution, test a log 10 transformation. Start or join a conversation to solve a problem or share tips and tricks with other JMP users. FoodandResource\$Economics\$\$\$\$\$University\$of\$Delaware\$\$\$\$\$Fall\$2010\$ 1\$\$\$\$\$

While both are above the 0.05 alpha risk, the Weibull distribution is the better distribution because there is a … Step Two: Use JMP to open the data .

You can get ^Class Data _ from the Stat111 website. While this rule of thumb is easy to compute, it should be used with caution as it can yield widely inaccurate estimates when the density is not close to being normal. variance (e.g., Levene’s and Brown-Forsythe which are both available in JMP).

Read blog posts, and download and share JMP add-ins, scripts and sample data. Conversely, a p-value greater than alpha suggests the data is normally distributed. This example will demonstrate testing raw data and transformed data for conformance with a normal distribution.