Things I wished I had said: - From the qqplot, the data on the girls had short tails at both ends. In layman terms this means the fev scores are concentrated around the center of the distribution compared to the normal; -For the boys, the distribution had short lower tail. In layman terms, this means the lower end scores on fev are higher compared to the normal. -If we had large outliers in fev, then the median would be a better choice than the mean for communicating the middleness of the data.
#barplot with categorical names. barplot(Data$cateogry1~Data$category2) #add this after the above command to make it pretty... #note: can change the y lim to control limit display area & the number in color can be anything as far as I know. Seems random... , main = "Title", xlab = "x axis title", ylab = "y axis title", ylim = c(0, 100),col=rainbow(10))
Thank you, I really enjoyed this presentation, the only thing that did not work for me was the is.factor for finding factors all came up false for some reason but I continued exercise without it and it seemed to work ok.
A p-value is connected to hypothesis testing. The QQ-plot (like other plots) is not performaing hypothesis testing so has no p-value. There are tests for normality.
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Things I wished I had said:
- From the qqplot, the data on the girls had short tails at both ends. In layman terms this means the fev scores are concentrated around the center of the distribution compared to the normal;
-For the boys, the distribution had short lower tail. In layman terms, this means the lower end scores on fev are higher compared to the normal.
-If we had large outliers in fev, then the median would be a better choice than the mean for communicating the middleness of the data.
You just helped me solve my question for my assignment. Has been searching for this so hours. Thanks. May Allah bless you :)
#barplot with categorical names.
barplot(Data$cateogry1~Data$category2)
#add this after the above command to make it pretty...
#note: can change the y lim to control limit display area & the number in color can be anything as far as I know. Seems random...
, main = "Title",
xlab = "x axis title",
ylab = "y axis title",
ylim = c(0, 100),col=rainbow(10))
Thank you, I really enjoyed this presentation, the only thing that did not work for me was the is.factor for finding factors all came up false for some reason but I continued exercise without it and it seemed to work ok.
very helpful. Thank you sir
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if the file is corrupted how do you fix it.
Is there a way for the Q-Q plot to show a p-value?
A p-value is connected to hypothesis testing. The QQ-plot (like other plots) is not performaing hypothesis testing so has no p-value. There are tests for normality.