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 Distribution?
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.
Let us ponder the unthinkable. Suppose the Normal Curve as we know it had never been discovered by Gauss? What would the statistical world of today look like?
(1)Of grave concern, sampling distributions of statistics would never APPROACH a normal distribution. What a revolting and depressing state of affairs.
(2) The Bivariate Normal Curve in 3D (i.e. the true bell curve) would never appear and be rotated on Internet web pages. Additionally, 3D-movies of this action would never be made and the 3D glasses industry would suffer immeasureably.
(3) The ubiquitous one-page standard normal curve table of selected percentiles would not appear in any statistics textbook. This table has been the hallmark of all statistics texts and statisticians would go stark raving mad not seeing this gem.
(4) The Statistical tee Shirt business would be defunct.
(5) Percentiles of sampling distributions of every imaginable statistic would all have to be developed individually and tabled because of (1). This would lead to monstrously thick textbooks with half of the book devoted just to tables. Oh my, the cost of a book to a student would be $500 or more! Also how would a student lug this to class?
(6) As the df-value of a t-curve increased, the tails of the curve would shrivel up and go to nothing and the points of inflection would disappear. That is, the curve would have a domed top and vertical sides. The end result would be nothing that you would recognize ( maybe look like a garbage can) and certainly far removed from a normal curve. But wait a minute, we don't have a normal curve anyway so who cares what we end up with?
(7) All curves or distributions would now be labelled ABNORMAL for a start and a whole new nomenclature for these would have to be developed to lend descriptive qualities and specificity to their appearance. What a nightmare and polyglot of new names!
(8)The nasty-looking formula for the probability density function of the normal curve along with its contained venerable "e" (the base of the natural logarithm system) would no longer appear in textbooks and scholarly works. This would be a horrific loss because an instructor could no longer flash this formula on the board for shock effect when introducing the normal curve to show students this curve is really not very "normal" mathematically.
(9) And last but not least, the multivariate normal distribution and all its applications would drop from the statistical scene. This could be the most heartbreaking loss of all since matrix algebra is the heart and sole of this technique with the necessity of the variance-covariance matrix employed in lieu of just a single variance in (8). In my estimation, this is the most elegant application of matrix algebra in all of mathematics and enables the field of mutivariate analysis to be explored with concise clarity and understanding.
*Well folks the above is just a start and contains only nine items because I did not want to mimic "David Letterman's Top Ten." You could add many more to this list. Putting it bluntly, the absence of the Normal Curve would be STATISTICAL ARMAGEDDON. So hug every Normal Curve you encounter and thank every statistician that has perpetuated its presence. The Normal Curve and Statistical Techniques are forever inseperable!
Did you hear about the big robbery several weeks ago at the Museum of Science and Industry in downtown Chicago?
Two masked and armed men stole six ORDINANTS near the middle of the large replica of the NORMAL distribution and the whole thing collapsed like a circus tent. When the maintenance staff discovered the disaster they were scared half silly. They finally decided to take all the remaining ORDINANTS, cut them into equal lengths, and reassemble everything into a model RECTANGULAR distribution. The next week NOT A SOLE visited the exhibit because it was so UNIFORM and boring!
*This calamity certainly has saddened the entire statistical world. No longer will visitors witness the two points of inflexion but will also miss the phenomenon of both tail-line curves approaching the score scale but never quite touching it. I think a donation would certainly be in order here for the restoration of the original exhibit to bring back the feeling of awe and elegance associated with the Normal Curve!