Ĭlick SigmaXL > Graphical Tools > Normal Probability.
Now we would like to stratify the customer satisfaction score by customer type and look at the normal probability plots.
Is this data normally distributed? See earlier histogram and descriptive statistics of Customer Satisfaction data. Probability Plot of Customer Satisfaction data is produced: Select Overall Satisfaction click Numeric Data The eminent statistician George Box uses a “Fat Pencil” test where the data, if covered by a fat pencil, can be considered normal! We can also see that the data is normal since the points fall within the normal probability plot 95% confidence intervals (confidence intervals will be discussed further in Analyze).Įnsure that entire data table is selected. Note that the data will not likely fall in a perfectly straight line. The data points follow the straight line fairly well, indicating that the data is normally distributed. A Normal Probability Plot of simulated random data is produced (again, your plot will be slightly different due to the random number generation):
Ensure that entire data table is selected.
Normal Random Data (1) Sheet, Click SigmaXL > Graphical Tools > Normal Probability Plots.
Create a normal probability plot of this data: Click.
05, the data is considered to be normal (interpretation of p-values will be discussed further in Analyze). If the p-value of the Anderson-Darling Normality test is greater than or equal to. Your data will be slightly different due to the random number generation:
Create a Histogram & Descriptive Statistics for this data.
Specify 1 Column, 100 Rows, Mean of 100 and Standard Deviation of 25 as shown below:
Create 100 random normal values as follows: Click SigmaXL > Data Manipulation > Random Data > Normal.