Can a skewed distribution still be considered a normal distribution?

Question

Can a skewed distribution still be considered a normal distribution? My data shows a normal bell curve with symmetric center but has a longer left tail. Would this still be considered a normal distribution?

 

 

Answer 1

Hello Anthony,

No, your distribution cannot possibly be considered normal. If your tail on the left is longer, we refer to that distribution as "negatively skewed," and in practical terms this means a higher level of occurrences took place at the high end of the distribution. Think of a statistics test administered where there were a great many easy scores and very few lower scores from your class. 

Characteristics of a normal distribution or normal bell curve are as follows:

Symmetric 
Unimodal       
Asymptotic 
The mean, median and mode are all the same. 

I am sure you know what symmetric means. Unimodal simply means you do not have a Bi-modal distribution. Asymptotic simply means that as the tails of the curve approach the x-axis they still will never touch the axis. 
Finally, you know - I am sure - what the mean, median and mode are. 


One last point that as a tutor I would not be doing my job if I did not briefly discuss: the kurtosis of the curve representing your distribution. 

This is another descriptor we use to describe a distribution or curve. Platykurtic refers to a distribution that is relatively flat compare to the normal bell curve. Leptokurtic refers to a distribution that is relatively peaked compared to a normal distribution. Finally, you have your normal distribution and bell curve. Please let me know if you need to know how to calculate the kurtosis of the curve. 

I hope this assists and wish you a great Sunday. Best wishes.