Political Science Rumors Topic: Some user claims CG@Harvard is a plagiarist
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Political Science Rumors Topic: Some user claims CG@Harvard is a plagiaristen-USSat, 20 Jul 2019 19:51:29 +0000http://bbpress.org/?v=1.0.2<![CDATA[Search]]>q
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PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403114
Sun, 05 May 2019 06:39:18 +0000PoliSci1403114@https://www.poliscirumors.com/<blockquote><p>HOW THE F*^K ARE YOU PEOPLE STILL TALKING ABOUT THIS?????????????<br />
Its been weeks. Let it go!
</p></blockquote>
<p>I actually agree with you at this point. I'm beyond bored of this. I proved my point, then found iron-clad support in a stats textbook. Most posters begrudgingly admitted I was right. Now I'm just getting the same questions that have already been answered over and over again. If some people are just incapable of admitting they were wrong, great, fine with me.
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403107
Sun, 05 May 2019 06:33:29 +0000PoliSci1403107@https://www.poliscirumors.com/<blockquote><p>Lavender:<br />
If Xbar is the random variable that you claim to use as a test statistic in 8.37.c, explain to us:<br />
1. Which other random variable are you conditioning Xbar on to get the conditional distribution that you’re taking about?<br />
2. What distribution does Xbar given this other random variable follow? Either explain how you would derive its density (and what that resulting density is), or if it’s a named distribution state its names and parameters.<br />
3. Which command and which arguments would you use (in R, or Stata) to get the relevant critical values?<br />
No theatrics, no lamentations, no insulting other posters. Just straight answers to the questions above. Thanks.
</p></blockquote>
<p>1. Cool, this has only been said 183,439 times. The estimated standard error. Exactly as C&B do in the example.</p>
<p>2. Also has been said maybe 18,345,101 times. It's a scaled t distribution. Thus, you compare the sample mean to the standard t critical values times the standard error. Exactly as C&B do in the example.</p>
<p>3. You calculate a critical t value and multiply it by the standard error. Very difficult code, but maybe you can figure it out. </p>
<p>I just love the pretense at the end that I haven't been crystal clear in my answers and argument from the very beginning. Hilarious stuff. I literally wrote down explicit equations (amazingly, the *exact* one you find in C&B) and gave consistent straight answers literally dozens of times. Doesn't matter to the diehard stats bros, though, who will never get it or deal with clear answers honestly.
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403105
Sun, 05 May 2019 06:27:27 +0000PoliSci1403105@https://www.poliscirumors.com/<blockquote><p>
If you read further, they say "The conditional distribution S1 given S=s is hypergeometric (n1+n2,n1,s)." It's not possible for a random variable to have two distributions. Once you have conditioned a random variable on another random variable, you have created a new random variable. But it's a moot point anyway because this is a test of equality of two Binomial parameters, and is completely irrelevant to whether one can use the sample mean as a test statistic.
</p></blockquote>
<p>"It's not possible for a random variable to have two distributions." Hahahahaha, it's not? How about if one distribution is conditional on something and the other is not? Ok, done. </p>
<p>Your inability to grasp the most elementary points is incredible. Yes, this example is relevant. For the millionth time, the example shows that you can use test statistics where the distribution is conditioned on an observed statistic, which is the only coherent objection anyone ever made to the sample mean or coefficient being used as a test statistic. This shows that that is actually fine. I'll just keep repeating this until you get it. How much time should I set aside? Is 10,000 years enough?
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403052
Sun, 05 May 2019 04:05:46 +0000PoliSci1403052@https://www.poliscirumors.com/<p>Lavender: </p>
<p>If Xbar is the random variable that you claim to use as a test statistic in 8.37.c, explain to us: </p>
<p>1. Which other random variable are you conditioning Xbar on to get the conditional distribution that you’re taking about? </p>
<p>2. What distribution does Xbar given this other random variable follow? Either explain how you would derive its density (and what that resulting density is), or if it’s a named distribution state its names and parameters.</p>
<p>3. Which command and which arguments would you use (in R, or Stata) to get the relevant critical values? </p>
<p>No theatrics, no lamentations, no insulting other posters. Just straight answers to the questions above. Thanks.
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403041
Sun, 05 May 2019 03:53:47 +0000PoliSci1403041@https://www.poliscirumors.com/<blockquote><p>
S1 is definitely NOT the test statistic. Here's another way to see why you're wrong: C&B say that the test statistic they construct by conditioning S1 on S follows a Hypergeometric(n1+n2,n1,s) distribution. S1 is Binomial (n1,p1). Not Hypergeometric. Ergo it can't be the test statistic. The test statistic is a new random variable which I denoted T above when I showed you how the derivation process works. Again, it's derived as P(T=t) = P(S1=s1 | S=s).<br />
C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Gee, real hard to tell if they use S1 as a test statistic, huh?<br />
You also seem not to understand how conditioning works or what a test statistic is. Try reading the beginning of that chapter by C&B for some basics. Your last two sentences are complete gibberish -- there's no new variable, no T, and that's not how test statistics work. Other than that, real close!<br />
You can't read. What they're saying is that they're using the *conditional* distribution of S1 given S=s as the test statistic. But in so doing they are implicitly creating a new random variable, different from S1, that acts as the test statistic, and has a Hypergeometric distribution (unlike S1, which is a Binomial).</p>
<p>C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Yeah, see where they talk about new variables there and how it's not S1 that's the test statistic. Oh, wait...<br />
Seriously, though, you seem not to have even a basic understanding of how this works. A test statistic involves an observed value that you compare to a distribution. You can't condition an observation itself on another variable. You condition the *distribution* on the other variable. So yes, S1 is the test statistic, just as C&B clearly state. The distribution is conditioned on S.
</p></blockquote>
<p>If you read further, they say "The conditional distribution S1 given S=s is hypergeometric (n1+n2,n1,s)." It's not possible for a random variable to have two distributions. Once you have conditioned a random variable on another random variable, you have created a new random variable. But it's a moot point anyway because this is a test of equality of two Binomial parameters, and is completely irrelevant to whether one can use the sample mean as a test statistic.
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403039
Sun, 05 May 2019 03:51:48 +0000PoliSci1403039@https://www.poliscirumors.com/<p>HOW THE F*^K ARE YOU PEOPLE STILL TALKING ABOUT THIS?????????????</p>
<p>Its been weeks. Let it go!
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403037
Sun, 05 May 2019 03:47:19 +0000PoliSci1403037@https://www.poliscirumors.com/<p>Stats bros: No, see, you can't use S1 as a test statist--</p>
<p>C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and..."</p>
<p>Stats bros: No! No! There must be a different variable called T that's the test stati--</p>
<p>C&B: "it is reasonable to use S1 as a test statistic and..."</p>
<p>Stats bros: No! My brain is melting! Help me!!</p>
<p>C&B: "S1 as a test statistic..."</p>
<p>Stats bros: It can't be... (gasp) ... (gurgle)
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1403035
Sun, 05 May 2019 03:40:21 +0000PoliSci1403035@https://www.poliscirumors.com/<blockquote><p>
S1 is definitely NOT the test statistic. Here's another way to see why you're wrong: C&B say that the test statistic they construct by conditioning S1 on S follows a Hypergeometric(n1+n2,n1,s) distribution. S1 is Binomial (n1,p1). Not Hypergeometric. Ergo it can't be the test statistic. The test statistic is a new random variable which I denoted T above when I showed you how the derivation process works. Again, it's derived as P(T=t) = P(S1=s1 | S=s).<br />
C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Gee, real hard to tell if they use S1 as a test statistic, huh?<br />
You also seem not to understand how conditioning works or what a test statistic is. Try reading the beginning of that chapter by C&B for some basics. Your last two sentences are complete gibberish -- there's no new variable, no T, and that's not how test statistics work. Other than that, real close!</p>
<p>You can't read. What they're saying is that they're using the *conditional* distribution of S1 given S=s as the test statistic. But in so doing they are implicitly creating a new random variable, different from S1, that acts as the test statistic, and has a Hypergeometric distribution (unlike S1, which is a Binomial).
</p></blockquote>
<p>C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Yeah, see where they talk about new variables there and how it's not S1 that's the test statistic. Oh, wait...</p>
<p>Seriously, though, you seem not to have even a basic understanding of how this works. A test statistic involves an observed value that you compare to a distribution. You can't condition an observation itself on another variable. You condition the *distribution* on the other variable. So yes, S1 is the test statistic, just as C&B clearly state. The distribution is conditioned on S.
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1402912
Sun, 05 May 2019 02:00:48 +0000PoliSci1402912@https://www.poliscirumors.com/<blockquote><p>
S1 is definitely NOT the test statistic. Here's another way to see why you're wrong: C&B say that the test statistic they construct by conditioning S1 on S follows a Hypergeometric(n1+n2,n1,s) distribution. S1 is Binomial (n1,p1). Not Hypergeometric. Ergo it can't be the test statistic. The test statistic is a new random variable which I denoted T above when I showed you how the derivation process works. Again, it's derived as P(T=t) = P(S1=s1 | S=s).</p>
<p>C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Gee, real hard to tell if they use S1 as a test statistic, huh?<br />
You also seem not to understand how conditioning works or what a test statistic is. Try reading the beginning of that chapter by C&B for some basics. Your last two sentences are complete gibberish -- there's no new variable, no T, and that's not how test statistics work. Other than that, real close!
</p></blockquote>
<p>You can't read. What they're saying is that they're using the *conditional* distribution of S1 given S=s as the test statistic. But in so doing they are implicitly creating a new random variable, different from S1, that acts as the test statistic, and has a Hypergeometric distribution (unlike S1, which is a Binomial).
</p>PoliSci on "Some user claims CG@Harvard is a plagiarist"
https://www.poliscirumors.com/topic/some-user-claims-cgharvard-is-a-plagiarist/page/15#post-1402893
Sun, 05 May 2019 01:51:01 +0000PoliSci1402893@https://www.poliscirumors.com/<blockquote><p>
S1 is definitely NOT the test statistic. Here's another way to see why you're wrong: C&B say that the test statistic they construct by conditioning S1 on S follows a Hypergeometric(n1+n2,n1,s) distribution. S1 is Binomial (n1,p1). Not Hypergeometric. Ergo it can't be the test statistic. The test statistic is a new random variable which I denoted T above when I showed you how the derivation process works. Again, it's derived as P(T=t) = P(S1=s1 | S=s).
</p></blockquote>
<p>C&B: "Given the value of S=s, it is reasonable to use S1 as a test statistic and reject H0 in favor of H1 for large values of S1..." Gee, real hard to tell if they use S1 as a test statistic, huh?</p>
<p>You also seem not to understand how conditioning works or what a test statistic is. Try reading the beginning of that chapter by C&B for some basics. Your last two sentences are complete gibberish -- there's no new variable, no T, and that's not how test statistics work. Other than that, real close!
</p>