Normal Probability Plots Explained (OpenIntro textbook supplement)

Topics covered in this video:
- Probability basics
- Disjoint / mutually independent
- Probability Distributions
- Complement
- Independence and probability

Video author, voice, and editor: David Diez.

[navjotsingh]

I loved this video. A nice follow up, would be a video where you go much deeper into the theory and explain the math behind these kind of plots. Thank you.

[Mahmoud-lixn]

Best explanation on Youtube for this topic, thank you.

[rffairchild]

I agree with other comments. This is the best explanation of this topic on YouTube

[riccardomattea]

Probably the best explanation video out there

[gunning]

Recipe for QQ-plot (quantile-quantile) in R:

## In R, a key observation is that the "pnorm" and "qnorm" functions are inverses of each other.
## To construct a QQ-plot of N observations (random samples here):
##
## Number of observations
nn <- 100
## the (sorted) data
the.sample <- sort(rnorm(nn))
## nn equally spaced probabilities
probs <- seq(from=1/nn, to=1-1/nn, length.out=nn)
quants <- qnorm(probs)
## QQplot
plot(quants, the.sample)
## R internal version
qqnorm(the.sample)
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REPLY

[aCllips]

Right vs. left skewness is depicted the opposite way. The picture on the left is skewed to the left, and the picture on the right is skewed to the right.

[Outlier_G]

I can't explain how best the video was. thanks 😊

[ankmeyester]

so, the x axis here is the z score values and the y axis is the actual values? and plotting it against one another as seen here, we should see how it lines up? the better the linearity, the more 'normal' the distribution?

[kittyxing]

Thanks for the video. How to generate the line for non-normal distributed data? I can understand that for the normal distributed data, the line has slope of STD and intercept of mean, then the x axis value is z score and y axis value is the actual data value. But how about the non-normal data set? how exactly to calculate the x axis value for each data point? how to calculate the y values for the straight line?

[Valerie-wszr]

just what I was searching for Nice job !!

[gunning]

In the textbook, I found the QQ-plot explanation to be lacking. Here, too, a number of key attributes are missing. First off, we must order the empirical observations (y-axis), as noted in previous comments. An explicit definition of "quantile" in earlier lectures would set the stage here, motivating "theoretical quantiles": the quantiles of the standard normal associated with the empirical probabilities (e.g. regularly spaced probabilites).

[shokhrukhabduahadov]

so why it is so? why dont u explain the reason for not fitting the line

[rishisingh]

Simply awesome! Thanks for shring this!

[sunilkumarsamji]

Well, The name is Normal probability plots. a) Why are they called Probability plots? b) Why the plot between the observed data and z score is supposed to be a straight line? Well I can understand if the data fits well its a measure of goodness of the fit, however, I dont understand why this has to be a straight line

[mmdsaleh]

Can we use the slope of the probability plot to measure the population variance of a sample?

[robert]

So, my data is skewed and non-normally distributed - What's to be done?
Do I perform some transformation to force normality, or do I rather just perform non-parametric tests?

[StellaNimas]

im doing my thesis rn, and the data is not normal, what to do with this? 😭😭

[allanmuganga]

Thanks for the video, it's been helpful. Kudos