GARY C. RAMSEYER'S FIRST INTERNET GALLERY OF STATISTICS JOKES BY TOPIC

A middle aged man suddenly contracted the dreaded disease kurtosis. Not only was this disease severely debilitating but he had the most virulent strain called leptokurtosis. A close friend told him his only hope was to see a statistical physician who specialized in this type of disease. The man was very fortunate to locate a specialist but he had to travel 800 miles for an appointment.

After a thorough physical exam, the statistical physician exclaimed, "Sir, you are indeed a lucky person in that the FDA has just approved a new drug called mesokurtimide for your illness. This drug will bulk you up the middle, smooth out your stubby tail, and restore your longer range of functioning. In other words, you will feel "NORMAL" again!"

*This shows how weird statistical humor can get. This is my own joke so go easy on the feedback!

THE TRUE BELL CURVE - The distribution of SUCCESS in life in relationship to AGE follows a true bell curve (Modified July 8, 2005):

At age 5 success is not peeing in your pants

At age 10 success is having friends in many many places

At age 16 success is having a driver's license and no moving violations

At age 20 success is having sex but harboring a variety of anxieties about it

At age 35 success is having money to pay cash for a turbocharged Porsche Carrera GT

At age 50 success is having money to pay cash for a turbocharged Porsche Carrera GT

At age 65 success is having sex but harboring a variety of anxieties about it

At age 70 success is having a driver's license and no moving violations

At age 75 success is having friends in many many places

At age 80 success is not peeing in your pants

*Thanks again to my colleague Jazzbo Johnson for suggesting this hilarious joke as it was related to him by a friend. It is displayed in gold because it represents the century mark for this Joke Gallery. What a milestone for this site! When I first conceived the notion of a Statistics Joke Gallery about four years ago there probably existed less than a handful of such jokes. At the time I thought that if 25 jokes could be accumulated in five years it would be a huge success. But WOW! We have now reached 100 and the site has become the envy of the statistical profession. Many thanks to all the contributors and keep the jokes coming.

THE BELL CURVE MEETS THE WELL CURVE

BELL: Fancy meeting you underneath me. I never did understand why someone perverted er,uh INVERTED me and created you. You aren't worth much!

WELL: You must have had your BELL rung! One of your allegedly famous applications is approximating a sampling distribution for certain hypothesis tests and the power curves for many of these tests are well, a WELL CURVE.

BELL: Oh WELL, I forgot that! More critically, WELL, your central tendancy is all messed up. Neither your mean or median represents you. Only your modes at the extremes characterize you. My curve is neat and tidy with all those indices identical. That is a real BELL RINGER!

WELL: WELL BELL, you are still living in the 18th and 19th centuries. You don't realize how distributions are changing. For example, the distribution of wealth is becoming WELL since the middle class is disappearing and only the extremly wealthy and the impoverished poor are increasing at the ends. Also, the approval ratings of elected officials is becoming WELL since feelings are polarized at the extremes with not much in the middle. I could go on and on.

BELL: WELL, you are threatening the limits of my practical range! Maybe, we can talk again under more NORMAL circumstances.

WELL: BELL you had your MOMENTS but we shall talk again. Meanwhile let us tell all statisticians to tie each set of our ends together and use the combined distributions as a CHRISTMAS TREE ORNAMENT! Good Day!

* Well folks, how many of you have even heard of the WELL CURVE? I was doing some Web surfing recently and found this interesting article by Jim Pinto printed in the San Diego Mensan, Aug. 2003. Seemingly, Mr. Pinto has coined the expression WELL CURVE for an inverted Normal Curve and touted its usefulness. Maybe this curve is becoming so prominant that it should now be included in statistics textbooks. Anyway, this conversation between the two curves is strictly my own little piece of "humorous" statistical nonsense.

How is a normal probability distribution like a lion?

They both have a MEAN MEW.

*Thanks are in order to Cynthia Gadol, an AP Statistics Teacher at Thomas Jefferson Classical Academy, for sending me this neat little pun. She claims she heard it years ago from Professor Rolf Bargmann at the University of Georgia. Cynthia, I have a reply for you: Q. How does a lion differ from a normal probablity distribution? A. A Lion can not go three standard deviations in pitch above or below its mean mu!! Oh well, this craziness makes the medicine go down a lot easier.

FOR THOSE WHO KNOW EVERYTHING THERE IS TO KNOW ABOUT STATISTICS

Question: Is the Normal Curve ever a Skewed Ditribution?

Answer: Always!! The Lower Half of the Normal Curve is Negatively Skewed and the Upper Half is Positively Skewed!!

*This is an unfair trick question. A Gestalt psychologist would urge you look at the normal curve as a single entity and not as two curves treated separately. But if you want to have some fun with your statistics professor ask him this question and see how he responds. Then after you give him the answer tell him he must begin thinking outside of the box. He may even give you extra credit!! I may be placed in a box and shipped away after this one.

In a Standard Normal Curve, the total area under the curve is ONE. Why then has it never been proven that no matter how far you go out away from the middle of the score scale at 0 in either direction there will always be some portion of the area under the curve beyond either point?

NO ONE HAS EVER WALKED OUT THAT FAR YET!!!

*Of course this was a bold face lie and it has been proven. In all seriousness though, it does seem like a contradiction that you can keep accumulating area under the curve as you keep moving out away from the middle and yet never exceed ONE. In simple language, just think of the concept of limits in mathematics. As you move in either direction toward minus infinity and plus infinity, the area under the curve does increase but only approaches ONE as a limit. Certainly not as exciting as proof of Fermat's Last Theorem a few years back but it does seem counterintuitive and excites your blood just a wee bit.

Why does the Normal Curve not need any degrees of freedom?

It is very content and smug about its status... It is ALREADY a t-Curve with infinite degrees of freedom so a few more would not help!

*Many students think of these two curves as separate entities because the Normal Curve is usually taught first. However, remember that the Normal Curve is the limiting case of a t-Curve with infinite degrees of freedom. Thus, the t-Curve, in reality, is the more general concept. In successive graphs of t-Curves, as the degrees of freedom increases starting with 3, the area in the tails shrink and the area in the middle of the curve increases approaching the Normal curve as a limit. Even at a degrees of freedom of 30 for the t-Curve in a moderately scaled drawing, graphs of the two curves are practically indistinguishable to the naked eye and the difference would only be detected by a high definition camera.