Testing – Dr. Gary C. Ramseyer

IDENTIFIER	TOPIC	JOKE
T1	Assumptions	There were a physicist, a circus strong man, and a statistician marooned on a desert island. A box of canned food washes ashore, and the question is how to open the cans. The physicist suggests dropping them from the trees so that they break open. The strong man says that’s too messy. Instead, he will rip the cans open with his bare hands. The statistician says that’s still too messy, but he knows how to open the cans without making a mess. “First,” he says “assume we have a can opener.” Electric or manual? Thanks Robert Frick for your contribution.
T2	Census	Knock! Knock! “Whose there?” (without opening the door) “The census taker.” “Go away — I don’t want my senses taken.” “No, you don’t understand, I just want to survey you.” “A statistical sample of one isn’t valid — go away.” “You aren’t the only one.” “So you are bothering a whole bunch of people, go away.” “Look you are unique and I don’t want to miss you in the survey.” “How do you know I’m unique when you haven’t surveyed me yet?” “O, I don’t know you are unique, but you might be.” “You mean you think I’m an oddball.” “No, maybe more like an outlier.” “Now you are calling me an out and outlier, go away.” “No, I mean you are far from the average Joe.” “I hope so, I’m Sally.” “Look Sally, we are trying to get population data, how many people live here?” “Gosh, how would I know, I think there are about 15 thousand in Smugville.” “No, I mean in this house!” “Oh, that’s a question of a different nature.” “So, how many?” “Sometimes one, sometimes two, sometimes four, now — go away.” “No, I need a precise number.” “Ok, how about 1.34” “How did you come up with that?” “I live here sometimes during the week, my sister visits me on weekends, and my mother visits me every second week, my two cats are sometimes here, and my … and that’s none of your business.” “Thanks Sally have a great day.” (censor taker wrote — “NO PERSONS LIVING HERE — UNOCCUPIED.” This is hilarious. It reminds me of the Abbott and Costello “Who’s on first?” routine. Also it has to be the longest Knock! Knock! joke ever written. Many thanks to Collin Carbno for sending this clever exchange from Saskatchewan Canada.
T3	Statistics	A statistician’s wife had twins. He was delighted. He rang the minister who was also delighted. “Bring them to church on Sunday and we’ll baptize them,” said the minister. “No,” replied the statistician. “Baptize one. We’ll keep the other as a control.” Sorry I lost the attribution on this one. Does anyone want to claim credit?
T4	Degrees Of Freedom	Two unbiased estimators were sitting in a bar. The first says, “So how do you like married life?” The other replies, “It’s pretty good if you don’t mind giving up that one degree of freedom!” A big thank you to Bert Bishop for submitting this.
T5	Degrees Of Freedom	A wise woman once said if all the statisticians in the world would claim all the DEGREES OF FREEDOM then the CEOs of all the corporations would have none. The Chiefs would be forced to go on a merit system tied to valid earnings and upon severance for poor performance would receive a black life preserver instead of a golden parachute. Moreover, if the statisticians do not take an infinity of degrees of freedom, many tables in textbooks would be one-row and lots of pages would be saved. It sounds like a win-win situation!
T6	Design	DESIGN CREED I believe in Analysis of Variance, a gift of the Almighty bestowed upon grateful mankind by Divine Providence through the Inspiration of the venerable Sir R. A. Fisher, Knight of the Realm, and his Disciples. I believe in the F-Ratio wherein the uppermost Mean Square Between overcomes the lowly Mean Square Within to yield Significant Blessings upon Faithful Researchers. I shall continue to maximize Experimental Variance and minimize Error Variance until the last of my Degrees of Freedom be spent and Divine Control shall see fit to lift my soul from this vale of Errors and Confirm my Hypothesis in that Blessed Realm where all Variance by Systematic and Error Variance be nought. Thanks to Hugh Foley for this contribution.
T7	Errors	We know that a Type 1 error is rejecting a true null hypothesis H0 and a Type II error is retaining a false H0. What then is a Type III error? Just so I have an odd number of errors for closure, it is a researcher paying absolutely no attention whatsoever to Type I and Type II errors in hypothesis testing!!!!
T8	F-Curve	An F-Curve was complaining to a Standard Normal Z-Curve one day at the shopping mall. The F-Curve said, “I am really envious of you. Here I am with a big bulge on one end and a drain pipe on the other end and you have a perfect symmetrical figure.” The Z-Curve replied, “Yes Mr. F but you are a far more prestigious curve in that you are the star in major applications like ANOVA and ANCOVA.” “Well Mr. Z, another thing that gripes my soul is that you never need any degrees of freedom and I always have to lug around two distinct DF-values on my back!” “Mr. F,” the Z-Curve responded, “that is very misleading. You know very well that a Z-Curve is nothing more than a mature T-Curve with an infinite number of degrees of freedom. Now that is a real load to carry. Take some away from me and I still have an infinity left!” The F-Curve paused shortly with his mouth wide open, then smiled broadly, and said in a conciliatory voice, “Mr. Z, Let’s go down to the ice cream shop and I will treat you to an Orange FFreeZZ! I guess statisticians really could not get by without either one of our curves.” What a nice ending to a story that had such a contentious beginning. Yes, statistics as a discipline could not exist without both the F- and the z-Curves.
T9	Fit Tests	Then there was the story of the sociological statistician who retired early from his teaching position at the university. He had grown up on the farm as a youth and still feeling quite chipper, decided to buy a large dairy farm in southern Wisconsin. After a short time the milk and cheese from his herd of cows became famous for miles around. Since his research at the university had demanded the use of many Chi-Square Goodness of Fit Tests, he thought he should commemorate all these procedures. Every year he invited the public to what became the most publicized and extravagant wine and cheese festival in Wisconsin. It was fondly called the GOODNESS OF TIT FEST!!!! Some of you experienced statisticians out there may well of heard this little reversal of letters before but not my story behind it. Maybe you heard it back in your graduate training days and all the snickers that accompanied it. I know I did. However, I always thought the original moniker was an awkward use of words and should have been renamed (Hear that Mr. Karl Pearson). The fact remains that this test is one of the most frequently appearing procedures in the literature, particularly in testing the independent of two nominal or ordinal variables.
T10	Hypothesis	Testing a statistical hypothesis is like flushing a water-saving toilet… It must be run past you a number of times before it becomes clear. I hope my crazy comparison does not stray too far from a vital statistical technique. The American Standard Company now has an innovative line of toilets that are essentially guaranteed to be plunger free. They are so high performing that they can flush a bucketful of golf balls in 1.6 flushes. Statistical methods should be so efficient, huh? See a funny movie on these toilets.
T11	Mean	These two friends decide to go rabbit hunting with bow and arrows. They convince their friend, the statistician, to come along since he doesn’t get out very much. The three wait patiently out in the woods for a rabbit to pass by. Suddenly, a rabbit bolts across a clearing some distance away and races toward a dense patch of trees. The first hunter whips out his bow, strings an arrow, and lets fly. “Darn,” he cries, “The arrow was a foot short.” Just then the rabbit bolts across the clearing from the other side of the woods. The second hunter whips out his bow, strings an arrow, and lets fly. “Darn” complains the second hunter, “the arrow went a foot long.” The rabbit once more emerges from the woods and races across the clearing. The statistician starts to raise his bow and then lowers it with a contemplative expression. He takes out the stub of a pencil, finds a crumpled envelope in a pants pocket, and quickly executes some calculations on the back of the envelope. The he looks up, smiling, as the rabbit disappears for the final time and waves the envelope in the direction of the other two hunters. “Look at this–if you take the mean distance that the arrows went, we got the rabbit!” A big thank you to Frederick M Siem.
T12	Mean	“When she told me I was average, she was just being mean.” A big thanks for this quickie to Mike Beckman who is working on his Ph.D at Virginia Tech. Just wondered Mike if one of your professors told you this?
T13	Mean	One day the variance and the standard deviation were engaged in a heated argument over which was the better measure of variability. The standard deviation shouted at the variance, “You are useless because you don’t even relate to the original score scale.” The variance glared back and yelled, “Oh yeah! You are totally worthless because you are far too radical.” Just then the mean deviation stepped between the two sides and pushed them both back. In a proud voice the mean deviation proclaimed, “You are both wrong! I am ABSOLUTELY the best measure of variability since both of you would be worth ZERO if you didn’t square your deviations!!!!” OK, this may not bring down the house with laughter. I still have a place in my heart for the antiquated mean deviation because of its intuitive nature. I believe students can see a rational for both S and S2 if MD is introduced first.
T14	Mean	As a biologist, a physicist, and a statistician are riding on a train through Wisconsin, they pass a herd of cows, one of which is completely white. “Oh look, there are white cows in Wisconsin,” says the biologist. “You mean,” says the physicist with an air of superiority, “there is at least one white cow in Wisconsin.” “No,” says the statistician, “there is at least one cow in Wisconsin that’s white on at least one side!” This is a new slant on an older stat joke! Thanks to Steve George of Amherst College who was told this by the late Julian Gibbs a chemist and former president of Amherst.
T15	Mean	Why are the mean, median, and mode like a valuable piece of real estate? LOCATION! LOCATION! LOCATION! All you beginning students of statistics just remember that measures of central tenancy are all POINTS on the score scale as opposed to measures of viability which are all DISTANCED on the score scale. Understand this maxim and you will always know where you are LOCATED!
T16	Mean	A friend of mine told me the other day that my statistics students must really hate me. The friend informed me that a student complained to him that my last test was so hard that EVERYONE scored below the mean and even the standard deviation was NEGATIVE! The student, however, told my friend he was a wee bit optimistic. His score was so low that he just knew that it would regress toward the mean on the next test!! Well, I am proud that my test set two new world records in the annals of statistics. On the other hand, maybe I should carefully go over the teaching notes that cover these topics. Anyway, a big thank you goes out to Steven C. Marcus for suggesting this joke. Steve, I hoped you don’t mind the embellishments that were tacked on.
T17	Regression Coefficients	What did one regression coefficient say to the other regression coefficient? I’m partial to you! A big thank you to James Jaccard of the State University of New York at Albany for sending me this tidbit.
T18	Sample Size	One day there was a fire in a wastebasket in the Dean’s office and in rushed a physicist, a chemist, and a statistician. The physicist immediately starts to work on how much energy would have to be removed from the fire to stop the combustion. The chemist works on which reagent would have to be added to the fire to prevent oxidation. While they are doing this, the statistician is setting fires to all the other wastebaskets in the office. “What are you doing?” they demanded. “Well, to solve the problem, obviously you need a large sample size” the statistician replies. This is one of my favorites. Thanks again to Hugh Foley.
T19	Sampling	A statistics professor was describing sampling theory to his class, explaining how a sample can be studied and used to generalize to a population. One of the students in the back of the room kept shaking his head. “What’s the matter?” asked the professor. “I don’t believe it,” said the student. “Why not study the whole population in the first place?” The professor continued explaining the ideas of random and representative samples. The student still shook his head. The professor launched into the mechanics of proportional stratified samples, randomized cluster sampling, the standard error of the mean, and the central limit theorem. The student remained unconvinced saying, “Too much theory, too risky, I couldn’t trust just a few numbers in place of ALL of them.” Attempting a more practical example, the professor then explained the scientific rigor and meticulous sample selection of the Nielsen television ratings which are used to determine how multiple millions of advertising dollars are spent. The student remained unimpressed saying, “You mean that just a sample of a few thousand can tell us exactly what over 250 MILLION people are doing?” Finally, the professor, somewhat disgruntled with the scepticism, replied, “Well, the next time you go to the campus clinic and they want to do a blood test…tell them that’s not good enough…tell them to TAKE IT ALL!!” This has to rank with the very best of the stat jokes and is also very instructive. Many thanks go out to Kenn(Doc) Finstuen for sending me this jewel. Kenn, who is a consulting statistician from San Antonian, Texas sent me a package of materials several years ago that were misplaced until recently. Sorry Kenn, this should have been in the Gallery much earlier.
T20	Sampling	When a statistician is pounding a nail with a hammer but misses the nail and hits his thumb, what do we call it? Sampling error. When a statistician is pounding a nail with a hammer but misses the nail and hits his thumb 10 CONSECUTIVE times, what do we call it? A Biased Statistic. How do we correct for the bias? Tell the statistician to place his thumb directly on the nail and then strike his thumb with the hammer!!! We have all hear the expression, “I’m all thumbs.” In this situation that is literally true. I hate to admit that during a weak moment this funnyism hit me. Anyway, thanks to all the reviewers who gave me two thumbs up in my mailbox on this one!
T21	Significance	An alien from a distant planet had a real problem. He had five groups of scores with their means and simply wanted to know which pairs of means differed significantly from one another. Since there were no statisticians on his planet he was told by a friend to visit planet earth where many scholars practiced this profession. He anxiously boarded his private spacecraft and made the long trek to earth. By this time the alien was beside himself with frustration and depression. He was ready to board his spacecraft and head home when a little gremlin whispered something in his ear, “Sir alien, there is a wise destitute old statistician of last resort who lives in a dilapidated old house on a hill. His methods are unorthodox but he is well known for wringing the last drop of meaning out of a set of data. You owe it to yourself to pay him a visit.” The downtrodden alien felt he had nothing to lose and decided to give it a try. The poor statistician welcomed the alien into his ramshackle home. The alien related his story how the F-test was significant but the follow-up procedures found NO significant differences between any two means. The statistician listened to his sad tale of woe and then winked at him with a broad smile. “Mr. Alien, I think I can guarantee some significant results. All you must do is forget your inhibitions, party it up by looking at other comparisons, and use the Scheffe S-test. Some good things will then happen to you.” The alien was quite skeptical but finally agreed to employ this strange test. The kind old statistician then invited him to the cellar of his home where he had stashed away a rusty old rotary calculator. The two sat down and the statistician feverishly pushed the keys. The gears whined, the numbers rolled on the many dials, and the carriage banged back and forth for what seemed like an eternity. Finally, after several hours, the statistician let out a howl, “Mr. Alien–I have it! i have found a significant difference.” The alien was trembling with sheer excitement and exclaimed “Please kind statistician, don’t keep me waiting. Tell me which pairs of means are different.” The statistician blurted out, “ONE-THIRD THE SUM OF MEANS ONE, TWO, AND FOUR IS SIGNIFICANTLY DIFFERENT FROM ONE-HALF THE SUM OF MEANS THREE AND FIVE!!” There were several moments of deadly silence. Then the alien’s mouth dropped and his face grew pale. Like a scared rabbit, he dashed toward his spacecraft and lifted off for home. As he put his craft in warp speed, he shook his head in disbelief. He vowed to visit a psychiatrist as soon as he got home and to NEVER, NEVER use numbers again. OK, all you students enrolled in a statistics course at the university level, is it possible for the circumstances in this little story to occur in real life? Please drop me an e-mail about my own crazy concocted story!
T22	Significance	What does a statistician call it when the heads of 10 rats are cut off and 1 survives? Nonsignificant. Thanks to Chad Hartry, a graduate student in my Statistics II class.
T23	Significance	Old statisticians never die they just become nonsignificant. This is my own quote. My students tell me I am only significant at the .10 level so how am I to interpret this?
T24	Significance	Why did the statistician take Viagra? Since his sample was large, he did not want to be rejected with a small p-=value and be declared practically nonsignificant!! Thanks to Philip J. Politis from the URI Fisheries Department for passing this joke along. However, I will not touch this with a ten-foot pole.
T25	Standard Deviation	A musician drove his statistician friend to a symphony concert one evening in his brand new mid-sized Chevy. When they arrived at the hall, all the parking spots were taken except one in a remote, dark corner of the lot. The musician quickly maneuvered his mid-sized Chevy into the space and they jumped out and walked toward the hall. They had only taken about ten steps when the musician suddenly realized he had lost his car key. The statistician was unconcerned because he knew the key had to be within one standard deviation of the car. They both retraced their steps and began searching the shadowed ground close to the driver’s door. After groping on his hands and knees for about a minute, the musician bounced to his feet and bolted several hundred yards toward a large street light near the back of the concert hall. He quickly got down on all fours and resumed his search in the brightly lit area. The statistician remained by the car dumbfounded knowing that the musician had absolutely zero quote of finding the key under the street light. Finally, after fifteen minutes,the statistician’s keen sense of logic got the best of him. He walked across the lot to the musician and asked, “Why in the world are you looking for your key under the street light? You lost it back in the far corner of the lot by your car!” The musician in his rumpled and stained suit slowly got to his feet and muttered angrily, “I KNOW, BUT THE LIGHT IS MUCH BETTER OVER HERE!!” Thanks to the late Professor Robert Rumery for telling me a variation of this story. If you are a musician, the lesson of this tale is: IF YOU GO MORE THAN THREE STANDARD DEVIATIONS FROM MIDDLE C YOU WILL NEVER FIND THE RIGHT KEY!