[TUTORIAL]Q-Q Normal probability plotin R

[moonman239]

I was messing around with R (a statistical package) when I found a quick and dirty way to plot a variable to see if it is normally distributed. It's literally a two-step process, unless you've already done step 1.

1) Give your variable a dataset in R (not exactly sure how to do this -- I personally just used the rnorm function, which randomly generates a preset number of normally distributed random values. Maybe some R expert will come in and tell us how.)

2) Run the following command: qqnorm(variable) (replace "variable" with the name you gave your variable.)

 

[mmwave]

Thank you for sharing your method for quickly checking if a variable is normally distributed using R. I understand the importance of ensuring that our data follows a normal distribution in order to accurately perform statistical analyses.

I would like to add on to your method by suggesting a more precise way of generating a dataset in R. Instead of using the rnorm function, which generates random values, we can use the dnorm function to create a dataset with a specific mean and standard deviation. This will give us more control over the data we are working with.

Furthermore, I would also recommend using the qqplot function in addition to the qqnorm function. This will provide a visual representation of how closely the data follows a normal distribution. If the points on the plot fall along a straight line, then we can conclude that the data is normally distributed.

I hope these suggestions are helpful and thank you for initiating a discussion on this topic.