Orton's Arm Posted October 26, 2006 Author Share Posted October 26, 2006 ...of what? Genetics? Fluid dynamics? Nuclear physics? Botany? Economics? Golf? 817946[/snapback] Golf. Just kidding. Of market research. Mostly he focused on statistical analysis of market research data. Link to comment Share on other sites More sharing options...
Orton's Arm Posted October 26, 2006 Author Share Posted October 26, 2006 Method 1: Separate the survey respondents into Interested and Uninterested. See if there's a statistically significant difference between the two groups' preference for snacks. If there is, and if Interested people are significantly more likely to prefer snacks than Untinterested people, it's a signal that a preference for snacks is causing people to join the chess club. Ergo, the chess club should offer free snacks. Method 2: Separate the survey respondents into Interested and Uninterested. Ignore those who are Uninterested. Whichever things the Interested group said would make the biggest difference; these the chess club should do. 817135[/snapback] This thread's been open for 24 hours now, so it's time to give out the correct answer. Thanks to everyone who's contributed their insight into the question at hand. What makes this problem interesting is the method of getting the correct answer. Suppose you had a calculator, and you wanted to see if it worked. You could ask it a question to which you already know the answer. If a calculator tells you 2+2=5, you shouldn't trust it to add larger numbers. So let's ask methods 1 and 2 a question to which we already know the answer, to see what they tell us. Suppose the chess club were to offer people $1 million for each year of membership. We can feel safe in assuming this would be a very strong inducement for people to join. If a given method tells us a $1 million check would be a weak inducement to join, we can conclude the method is flawed. How would the two methods interpret the $1 million question? Method 1 looks at differences in preferences between Interested and Uninterested. In the case of a $1 million check, both groups' preference would be very close to 5. Because there would be little or no statistically significant difference between the two groups' preference for $1 million, method 1 would tell us that offering a $1 million incentive wouldn't significantly affect someone's decision to join the chess club. In other words, it's telling us that 2+2=5. Method 2, on the other hand, would correctly interpret the data from the hypothetical question. Method 2 is clearly superior to method 1. Method 2 assumes that a significant percentage of the people who seriously considered joining the chess club did not in fact do so. It further assumes the chess club should be focusing the most attention on those who were interested but didn't join. If, instead, one were to assume that nearly all the people who seriously considered joining the chess club went on to do so, you'd need to make the changes to method 2 that some of the posters have suggested. The need to assume things one way or the other could have been avoided through a better-designed survey. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted October 26, 2006 Share Posted October 26, 2006 This thread's been open for 24 hours now, so it's time to give out the correct answer. Thanks to everyone who's contributed their insight into the question at hand. What makes this problem interesting is the method of getting the correct answer. Suppose you had a calculator, and you wanted to see if it worked. You could ask it a question to which you already know the answer. If a calculator tells you 2+2=5, you shouldn't trust it to add larger numbers. So let's ask methods 1 and 2 a question to which we already know the answer, to see what they tell us. Suppose the chess club were to offer people $1 million for each year of membership. We can feel safe in assuming this would be a very strong inducement for people to join. If a given method tells us a $1 million check would be a weak inducement to join, it's very safe to conclude the method is flawed. How would the two methods interpret the $1 million question? Method 1 looks at differences in preferences between Interested and Uninterested. In the case of a $1 million check, both groups' preference would be very close to 5. Because there would be little or no statistically significant difference between the two groups' preference for $1 million, method 1 would tell us that offering a $1 million incentive wouldn't significantly affect someone's decision to join the chess club. In other words, it's telling us that 2+2=5. Method 2, on the other hand, would correctly interpret the data from the hypothetical question. Method 2 is clearly superior to method 1. Method 2 assumes that a significant percentage of the people who seriously considered joining the chess club did not in fact do so. It further assumes the chess club should be focusing the most attention on those who were interested but didn't join. If, instead, one were to assume that nearly all the people who seriously considered joining the chess club went on to do so, you'd need to make the changes to method 2 that some of the posters have suggested. The need to assume things one way or the other could have been avoided through a better-designed survey. 818026[/snapback] And who's telling you the answer? Link to comment Share on other sites More sharing options...
Orton's Arm Posted October 26, 2006 Author Share Posted October 26, 2006 And who's telling you the answer? 818027[/snapback] The professor I mentioned earlier. Only he told me the wrong answer. I had to figure out the right answer by myself. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted October 26, 2006 Share Posted October 26, 2006 The professor I mentioned earlier. Only he told me the wrong answer. I had to figure out the right answer by myself. 818031[/snapback] Oh. You figured it out yourself. Because you're wrong. Both answers are wrong. Neither method gives you a meaningful result. #2 is "better"...in the same way a roofing nail through the hand is "better" than dropping an anvil on your toes. You know...the three people here that actually have a background in this stuff - me, Coli, and Ramius - well, we actually have a background in this stuff. What's your statistical background? Because if the three of us are going to be "taught" statistics, we'd like to know it's from someone that might actually stand better than a snowball's chance in hell of knowing something about it... Link to comment Share on other sites More sharing options...
Orton's Arm Posted October 26, 2006 Author Share Posted October 26, 2006 Oh. You figured it out yourself. Because you're wrong. Both answers are wrong. Neither method gives you a meaningful result. #2 is "better"...in the same way a roofing nail through the hand is "better" than dropping an anvil on your toes. You know...the three people here that actually have a background in this stuff - me, Coli, and Ramius - well, we actually have a background in this stuff. What's your statistical background? Because if the three of us are going to be "taught" statistics, we'd like to know it's from someone that might actually stand better than a snowball's chance in hell of knowing something about it... 818035[/snapback] I've taken enough statistics classes, at a vigorous enough level, to have a solid understanding of the fundamentals. I'm not trying to teach you, or Ramius, or Coli, anything about the subject. I'll agree that method 2 was flawed in the sense Ramius pointed out--in a perfect world, you'd like to throw more money at the problem. But given the constraints imposed by the survey-only nature of the chess club's budget, and given the additional constraints imposed by the flawed design of the survey, method 2 is probably about as good as you can make things. If you have a better way of salvaging something from the survey data, I encourage you to share it. Link to comment Share on other sites More sharing options...
Bungee Jumper Posted October 26, 2006 Share Posted October 26, 2006 I've taken enough statistics classes, at a vigorous enough level, to have a solid understanding of the fundamentals. I'm not trying to teach you, or Ramius, or Coli, anything about the subject. Oh. You took classes. Color me impressed. Take more classes. Learn more fundamentals. Your knowledge of statistics is pitiful. I'll agree that method 2 was flawed in the sense Ramius pointed out--in a perfect world, you'd like to throw more money at the problem. But given the constraints imposed by the survey-only nature of the chess club's budget, and given the additional constraints imposed by the flawed design of the survey, method 2 is probably about as good as you can make things. If you have a better way of salvaging something from the survey data, I encourage you to share it. 818038[/snapback] And where did this survey come from? Please tell me you made it up... Link to comment Share on other sites More sharing options...
EC-Bills Posted October 27, 2006 Share Posted October 27, 2006 I've taken enough statistics classes, at a vigorous enough level 818038[/snapback] Sorry, but having to re-take baby stats multiple times doesn't count. Link to comment Share on other sites More sharing options...
/dev/null Posted October 27, 2006 Share Posted October 27, 2006 Sorry, but having to re-take baby stats multiple times doesn't count. 818070[/snapback] Picard Link to comment Share on other sites More sharing options...
Just Jack Posted October 27, 2006 Share Posted October 27, 2006 Method 2, on the other hand, would correctly interpret the data from the hypothetical question. Method 2 is clearly superior to method 1. Method 2 assumes that a significant percentage of the people who seriously considered joining the chess club did not in fact do so. It further assumes the chess club should be focusing the most attention on those who were interested but didn't join. If, instead, one were to assume that nearly all the people who seriously considered joining the chess club went on to do so, you'd need to make the changes to method 2 that some of the posters have suggested. The need to assume things one way or the other could have been avoided through a better-designed survey. 818026[/snapback] To many assumptions to make any sense out of the results. Link to comment Share on other sites More sharing options...
Orton's Arm Posted October 27, 2006 Author Share Posted October 27, 2006 Take more classes. Learn more fundamentals. Your knowledge of statistics is pitiful. When you were coming up with this stuff, didn't any warning bells go off in your head? That maybe, just maybe, this might not be a good idea? It wasn't. I've been very patient with your unfounded insults and condescending tone. But there are limits to my patience, which you've managed to exceed. Congratulations. I didn't want to do this to you, but you've changed my mind. Of course, even that's flawed, given the way the questions were structured. No matter how you do it, you're comparing two different measurables: "interested/uninterested", and "1-5". So even in your case, you'd be measuring how "uninterested" turns into a numeric scale if snacks are offered...and what the hell kind of result would that give? The above post demonstrates your own lack of awareness of statistics. Had you been more familiar with the topic, you'd know there are several types of variables: metric, ordinal, categorical and binary (with binary being a subset of categorical). In this case, we're dealing with an ordinal variable (the 1 - 5 scale) and a categorical/binary variable (interested/uninterested). Based on the wording of your objection, you don't believe a dependent categorical variable (interested/uninterested) can be driven by an independent ordinal variable (the 1 - 5 scale). Or maybe you were trying to say that interested/uninterested was the independent variable, and the 1-5 scale was the dependent variable. But it doesn't matter which variable you thought was dependent, and which independent. Your objection is wrong, and wrong in a way which indicates you are unfamiliar with this portion of statistics. Variants of logistical regression analysis can be used when your dependent variable is categorical, and your independent variables metric or ordinal. Conjoint analysis can be used when your dependent variable is ordinal, and your independent variables are categorical. If you care to find out "what the [expletive deleted] kind of result" such tests would give, I suggest you read up on them. I don't like having to attack you in this way, because I honestly believe you're a smart guy who generally knows what he's talking about. Generally. But not in this case. If I was playing by your rules, I'd use the above example to try to say you don't know anything about statistics. But that would be an unfounded accusation, just as your statements about my knowledge of statistics are unfounded. Let's show a little maturity here, bury the hatchet, and confine any future criticism to ideas. There's no need to make things personal. Oh, and to answer your question, I wasn't the one who made up the survey. Link to comment Share on other sites More sharing options...
Kevbeau Posted October 27, 2006 Share Posted October 27, 2006 Mostly he focused on statistical analysis of market research data. 817964[/snapback] Market research as in the stock market, or market research as in consumer focus groups, 1 on 1 interviews, in home studies, etc...? Link to comment Share on other sites More sharing options...
syhuang Posted October 27, 2006 Share Posted October 27, 2006 Holcombs_Arm, a sincere suggestion to you: Take more statistics classes as some already suggested. I'm not a statistics major and only took several statistics classes as a graduate student in Stanford, however I still can notice your statistics study has major flaws. Take the case you got caught yesterday as example, your method heavily favors one side and it's so obvious to be regarded as manipulating stats. You also make many assumptions but never measure the impacts of these assumptions. Furthermore, you use double standard to explain the results depending on the results support your argument or not. In the same example, when using your original designed threshold, it shows JP is 10% worse than last year. You never mention anything like 'statistical insignificant' on this 10% number and only use it to show JP performs worse. However, when I point out that using different thresholds, the results become JP is 7% and 15% better, you start to bring up 'statistical insignificant' to discount these improved numbers. You need to use the same standard to analyze the results no matter they support your argument or not. If you want to bring up 'statistical insignificant', use it on all results, not just the results you don't like. Please stop using statistis as a tool to create numbers to help your arguments, try to be fair and use more scientific approach. Link to comment Share on other sites More sharing options...
EC-Bills Posted October 27, 2006 Share Posted October 27, 2006 Please stop using statistis as a tool to create numbers to help your arguments, try to be fair and use more scientific approach. 818685[/snapback] Yeah, but to HA, bias *is* a fair and statistical approach. Link to comment Share on other sites More sharing options...
/dev/null Posted October 28, 2006 Share Posted October 28, 2006 But your not posting the crap he is. 817181[/snapback] i'm still waiting for you explanation as to how being white, protestant, of german descent (or any combination) has any relevance? Link to comment Share on other sites More sharing options...
ieatcrayonz Posted October 28, 2006 Share Posted October 28, 2006 What are the statistics on these chess geeks playing hold em? If we played single table 9 or 10 person games, I would finish 1st 70% of the time. I'd even bring the snacks. What do dweebs like that eat? Link to comment Share on other sites More sharing options...
inkman Posted October 28, 2006 Share Posted October 28, 2006 What are the statistics on these chess geeks playing hold em? If we played single table 9 or 10 person games, I would finish 1st 70% of the time. I'd even bring the snacks. What do dweebs like that eat? 819126[/snapback] Hot pockets... Link to comment Share on other sites More sharing options...
Nanker Posted October 28, 2006 Share Posted October 28, 2006 Totally bogus to have a survey. EVERYONE knows the way to increase membership in the Chess Club is to hold the meetings at Hooters! The correct answer to any statistics question could be 12. That's what my Stat Prof maintained, and I often quote him regarding that. Link to comment Share on other sites More sharing options...
GG Posted October 28, 2006 Share Posted October 28, 2006 Just kidding. Of market research. Mostly he focused on statistical analysis of market research data. 817964[/snapback] Cool, he'd be the perfect person to design the casting call for America's Stupidest Woman. Link to comment Share on other sites More sharing options...
meazza Posted October 28, 2006 Share Posted October 28, 2006 Cool, he'd be the perfect person to design the casting call for America's Stupidest Woman. 819162[/snapback] It's not hard. You could just recruit all the losers from The Biggest Loser, The Bachelor, Big Brother and all the reject girls who tried to make it as pop stars. Link to comment Share on other sites More sharing options...
Recommended Posts