Why does this expression simplify as such?General linear hypothesis test statistic: equivalence of two...

Why does this expression simplify as such?

How can I write humor as character trait?

Does Doodling or Improvising on the Piano Have Any Benefits?

Is this toilet slogan correct usage of the English language?

Which was the first story featuring espers?

A variation to the phrase "hanging over my shoulders"

How do I fix the group tension caused by my character stealing and possibly killing without provocation?

Why does AES have exactly 10 rounds for a 128-bit key, 12 for 192 bits and 14 for a 256-bit key size?

What is Cash Advance APR?

How to draw a matrix with arrows in limited space

Is this part of the description of the Archfey warlock's Misty Escape feature redundant?

Change the color of a single dot in `ddot` symbol

How to explain what's wrong with this application of the chain rule?

C++ copy constructor called at return

Can I turn my anal-retentiveness into a career?

Multiplicative persistence

How to preserve electronics (computers, iPads and phones) for hundreds of years

Why is the Sun approximated as a black body at ~ 5800 K?

Circuit Analysis: Obtaining Close Loop OP - AMP Transfer function

Can you use Vicious Mockery to win an argument or gain favours?

When were female captains banned from Starfleet?

What is going on with gets(stdin) on the site coderbyte?

Make a Bowl of Alphabet Soup

A Trivial Diagnosis



Why does this expression simplify as such?


General linear hypothesis test statistic: equivalence of two expressionsSlope Derivation for the variance of a least square problem via Matrix notationCovariance of OLS estimator and residual = 0. Where is the mistake?A doubt on SUR modelWhy trace of $I−X(X′X)^{-1}X′$ is $n-p$ in least square regression when the parameter vector $beta$ is of p dimensions?Getting the posterior for Bayesian linear regression with a flat priorDistribution of coefficients in linear regressionFitted values and residuals: are they random vectors?Proving that Covariance of residuals and errors is zeroWhat is the relationship of long and short regression when we have an intercept?













3












$begingroup$


I'm reading through my professor's lecture notes on the multiple linear regression model and at one point he writes the following:



$$E[(b-beta)e']=E[(X'X)^{-1}epsilonepsilon'M_{[X]}]. $$



In the above equation, $b$, $beta$, $e$, and $epsilon$ are all vectors, $X$ is a regressor matrix and $M$ is the residual maker matrix. In general, I have no idea why these expressions are equivalent, and I'm particularly confused at how the $e$ vector disappears and the $epsilon$ vector appears.










share|cite|improve this question











$endgroup$

















    3












    $begingroup$


    I'm reading through my professor's lecture notes on the multiple linear regression model and at one point he writes the following:



    $$E[(b-beta)e']=E[(X'X)^{-1}epsilonepsilon'M_{[X]}]. $$



    In the above equation, $b$, $beta$, $e$, and $epsilon$ are all vectors, $X$ is a regressor matrix and $M$ is the residual maker matrix. In general, I have no idea why these expressions are equivalent, and I'm particularly confused at how the $e$ vector disappears and the $epsilon$ vector appears.










    share|cite|improve this question











    $endgroup$















      3












      3








      3





      $begingroup$


      I'm reading through my professor's lecture notes on the multiple linear regression model and at one point he writes the following:



      $$E[(b-beta)e']=E[(X'X)^{-1}epsilonepsilon'M_{[X]}]. $$



      In the above equation, $b$, $beta$, $e$, and $epsilon$ are all vectors, $X$ is a regressor matrix and $M$ is the residual maker matrix. In general, I have no idea why these expressions are equivalent, and I'm particularly confused at how the $e$ vector disappears and the $epsilon$ vector appears.










      share|cite|improve this question











      $endgroup$




      I'm reading through my professor's lecture notes on the multiple linear regression model and at one point he writes the following:



      $$E[(b-beta)e']=E[(X'X)^{-1}epsilonepsilon'M_{[X]}]. $$



      In the above equation, $b$, $beta$, $e$, and $epsilon$ are all vectors, $X$ is a regressor matrix and $M$ is the residual maker matrix. In general, I have no idea why these expressions are equivalent, and I'm particularly confused at how the $e$ vector disappears and the $epsilon$ vector appears.







      regression multiple-regression linear-model residuals






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited 3 hours ago









      Benjamin Christoffersen

      1,264519




      1,264519










      asked 4 hours ago









      DavidDavid

      24311




      24311






















          2 Answers
          2






          active

          oldest

          votes


















          3












          $begingroup$

          I am assuming $b$ is the OLS estimate of $beta$ and $e$ is the corresponding estimate of $epsilon$. Also I believe you have a typo above in your expression, as there should be $X'$ in front of $epsilon epsilon'$ and behind $(X'X)^{-1}$.



          Start with the definition of $b$:
          $$b=(X'X)^{-1}X'Y.$$
          Replacing $Y$ with $Xbeta+epsilon$ in our expression above, we get
          $$b=(X'X)^{-1}X'(Xbeta+epsilon)=beta+(X'X)^{-1}X'epsilon.$$
          It follows that
          $$b-beta = (X'X)^{-1}X'epsilon$$



          Now turn to the defintion of $e$:
          $$e=Y-hat{Y}=Y-Xb=Y-X(X'X)^{-1}X'Y.$$



          Notice $X(X'X)^{-1}X'$ is the projection matrix for $X$, which we will denote with $P_{[X]}$.
          Replacing this in our expression for $e,$ we get
          $$e=(I-P_{[X]})Y=M_{[X]}Y.$$
          Replacing $Y$ in the expression above with $Xbeta+epsilon$, we get
          $$e=M_{[X]}(Xbeta+epsilon)=M_{[X]}epsilon,$$
          since $M_{[X]}X$ is a matrix of zeros.



          Post-multiplying $b-beta$ with $e'$, we get
          $$(b-beta)e'=(X'X)^{-1}X'epsilon epsilon' M_{[X]},$$
          since $e'=epsilon'M_{[X]}.$






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Ah. The key thing I was missing was what you wrote in the last line.
            $endgroup$
            – David
            2 hours ago



















          3












          $begingroup$

          Assuming that the coefficient estimator $b$ is calculated by OLS estimation, you have:



          $$begin{equation} begin{aligned}
          b-beta
          &= (X'X)^{-1} X'y - beta \[6pt]
          &= (X'X)^{-1} X'(X beta + epsilon)- beta \[6pt]
          &= (X'X)^{-1} (X'X) beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= (X'X)^{-1} X' epsilon. \[6pt]
          end{aligned} end{equation}$$



          Presumably $e$ is the residual vector (different to the error vector $epsilon$) so we have $e = M_{[X]} Y = M_{[X]} epsilon$. Substituting this vector gives:



          $$begin{equation} begin{aligned}
          (b-beta) e'
          &= (X'X)^{-1} X' epsilon (M_{[X]} epsilon)' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}. \[6pt]
          end{aligned} end{equation}$$



          (The last step follows from the fact that $M_{[X]}$ is a symmetric matrix.) So the expression given by your professor is missing the $X'$ term.






          share|cite|improve this answer









          $endgroup$









          • 2




            $begingroup$
            Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
            $endgroup$
            – dlnB
            2 hours ago






          • 1




            $begingroup$
            @dlnb: Jinx! Buy me a coke!
            $endgroup$
            – Ben
            2 hours ago











          Your Answer





          StackExchange.ifUsing("editor", function () {
          return StackExchange.using("mathjaxEditing", function () {
          StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
          StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
          });
          });
          }, "mathjax-editing");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "65"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: false,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: null,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstats.stackexchange.com%2fquestions%2f398797%2fwhy-does-this-expression-simplify-as-such%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          2 Answers
          2






          active

          oldest

          votes








          2 Answers
          2






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          3












          $begingroup$

          I am assuming $b$ is the OLS estimate of $beta$ and $e$ is the corresponding estimate of $epsilon$. Also I believe you have a typo above in your expression, as there should be $X'$ in front of $epsilon epsilon'$ and behind $(X'X)^{-1}$.



          Start with the definition of $b$:
          $$b=(X'X)^{-1}X'Y.$$
          Replacing $Y$ with $Xbeta+epsilon$ in our expression above, we get
          $$b=(X'X)^{-1}X'(Xbeta+epsilon)=beta+(X'X)^{-1}X'epsilon.$$
          It follows that
          $$b-beta = (X'X)^{-1}X'epsilon$$



          Now turn to the defintion of $e$:
          $$e=Y-hat{Y}=Y-Xb=Y-X(X'X)^{-1}X'Y.$$



          Notice $X(X'X)^{-1}X'$ is the projection matrix for $X$, which we will denote with $P_{[X]}$.
          Replacing this in our expression for $e,$ we get
          $$e=(I-P_{[X]})Y=M_{[X]}Y.$$
          Replacing $Y$ in the expression above with $Xbeta+epsilon$, we get
          $$e=M_{[X]}(Xbeta+epsilon)=M_{[X]}epsilon,$$
          since $M_{[X]}X$ is a matrix of zeros.



          Post-multiplying $b-beta$ with $e'$, we get
          $$(b-beta)e'=(X'X)^{-1}X'epsilon epsilon' M_{[X]},$$
          since $e'=epsilon'M_{[X]}.$






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Ah. The key thing I was missing was what you wrote in the last line.
            $endgroup$
            – David
            2 hours ago
















          3












          $begingroup$

          I am assuming $b$ is the OLS estimate of $beta$ and $e$ is the corresponding estimate of $epsilon$. Also I believe you have a typo above in your expression, as there should be $X'$ in front of $epsilon epsilon'$ and behind $(X'X)^{-1}$.



          Start with the definition of $b$:
          $$b=(X'X)^{-1}X'Y.$$
          Replacing $Y$ with $Xbeta+epsilon$ in our expression above, we get
          $$b=(X'X)^{-1}X'(Xbeta+epsilon)=beta+(X'X)^{-1}X'epsilon.$$
          It follows that
          $$b-beta = (X'X)^{-1}X'epsilon$$



          Now turn to the defintion of $e$:
          $$e=Y-hat{Y}=Y-Xb=Y-X(X'X)^{-1}X'Y.$$



          Notice $X(X'X)^{-1}X'$ is the projection matrix for $X$, which we will denote with $P_{[X]}$.
          Replacing this in our expression for $e,$ we get
          $$e=(I-P_{[X]})Y=M_{[X]}Y.$$
          Replacing $Y$ in the expression above with $Xbeta+epsilon$, we get
          $$e=M_{[X]}(Xbeta+epsilon)=M_{[X]}epsilon,$$
          since $M_{[X]}X$ is a matrix of zeros.



          Post-multiplying $b-beta$ with $e'$, we get
          $$(b-beta)e'=(X'X)^{-1}X'epsilon epsilon' M_{[X]},$$
          since $e'=epsilon'M_{[X]}.$






          share|cite|improve this answer









          $endgroup$













          • $begingroup$
            Ah. The key thing I was missing was what you wrote in the last line.
            $endgroup$
            – David
            2 hours ago














          3












          3








          3





          $begingroup$

          I am assuming $b$ is the OLS estimate of $beta$ and $e$ is the corresponding estimate of $epsilon$. Also I believe you have a typo above in your expression, as there should be $X'$ in front of $epsilon epsilon'$ and behind $(X'X)^{-1}$.



          Start with the definition of $b$:
          $$b=(X'X)^{-1}X'Y.$$
          Replacing $Y$ with $Xbeta+epsilon$ in our expression above, we get
          $$b=(X'X)^{-1}X'(Xbeta+epsilon)=beta+(X'X)^{-1}X'epsilon.$$
          It follows that
          $$b-beta = (X'X)^{-1}X'epsilon$$



          Now turn to the defintion of $e$:
          $$e=Y-hat{Y}=Y-Xb=Y-X(X'X)^{-1}X'Y.$$



          Notice $X(X'X)^{-1}X'$ is the projection matrix for $X$, which we will denote with $P_{[X]}$.
          Replacing this in our expression for $e,$ we get
          $$e=(I-P_{[X]})Y=M_{[X]}Y.$$
          Replacing $Y$ in the expression above with $Xbeta+epsilon$, we get
          $$e=M_{[X]}(Xbeta+epsilon)=M_{[X]}epsilon,$$
          since $M_{[X]}X$ is a matrix of zeros.



          Post-multiplying $b-beta$ with $e'$, we get
          $$(b-beta)e'=(X'X)^{-1}X'epsilon epsilon' M_{[X]},$$
          since $e'=epsilon'M_{[X]}.$






          share|cite|improve this answer









          $endgroup$



          I am assuming $b$ is the OLS estimate of $beta$ and $e$ is the corresponding estimate of $epsilon$. Also I believe you have a typo above in your expression, as there should be $X'$ in front of $epsilon epsilon'$ and behind $(X'X)^{-1}$.



          Start with the definition of $b$:
          $$b=(X'X)^{-1}X'Y.$$
          Replacing $Y$ with $Xbeta+epsilon$ in our expression above, we get
          $$b=(X'X)^{-1}X'(Xbeta+epsilon)=beta+(X'X)^{-1}X'epsilon.$$
          It follows that
          $$b-beta = (X'X)^{-1}X'epsilon$$



          Now turn to the defintion of $e$:
          $$e=Y-hat{Y}=Y-Xb=Y-X(X'X)^{-1}X'Y.$$



          Notice $X(X'X)^{-1}X'$ is the projection matrix for $X$, which we will denote with $P_{[X]}$.
          Replacing this in our expression for $e,$ we get
          $$e=(I-P_{[X]})Y=M_{[X]}Y.$$
          Replacing $Y$ in the expression above with $Xbeta+epsilon$, we get
          $$e=M_{[X]}(Xbeta+epsilon)=M_{[X]}epsilon,$$
          since $M_{[X]}X$ is a matrix of zeros.



          Post-multiplying $b-beta$ with $e'$, we get
          $$(b-beta)e'=(X'X)^{-1}X'epsilon epsilon' M_{[X]},$$
          since $e'=epsilon'M_{[X]}.$







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered 2 hours ago









          dlnBdlnB

          81011




          81011












          • $begingroup$
            Ah. The key thing I was missing was what you wrote in the last line.
            $endgroup$
            – David
            2 hours ago


















          • $begingroup$
            Ah. The key thing I was missing was what you wrote in the last line.
            $endgroup$
            – David
            2 hours ago
















          $begingroup$
          Ah. The key thing I was missing was what you wrote in the last line.
          $endgroup$
          – David
          2 hours ago




          $begingroup$
          Ah. The key thing I was missing was what you wrote in the last line.
          $endgroup$
          – David
          2 hours ago













          3












          $begingroup$

          Assuming that the coefficient estimator $b$ is calculated by OLS estimation, you have:



          $$begin{equation} begin{aligned}
          b-beta
          &= (X'X)^{-1} X'y - beta \[6pt]
          &= (X'X)^{-1} X'(X beta + epsilon)- beta \[6pt]
          &= (X'X)^{-1} (X'X) beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= (X'X)^{-1} X' epsilon. \[6pt]
          end{aligned} end{equation}$$



          Presumably $e$ is the residual vector (different to the error vector $epsilon$) so we have $e = M_{[X]} Y = M_{[X]} epsilon$. Substituting this vector gives:



          $$begin{equation} begin{aligned}
          (b-beta) e'
          &= (X'X)^{-1} X' epsilon (M_{[X]} epsilon)' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}. \[6pt]
          end{aligned} end{equation}$$



          (The last step follows from the fact that $M_{[X]}$ is a symmetric matrix.) So the expression given by your professor is missing the $X'$ term.






          share|cite|improve this answer









          $endgroup$









          • 2




            $begingroup$
            Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
            $endgroup$
            – dlnB
            2 hours ago






          • 1




            $begingroup$
            @dlnb: Jinx! Buy me a coke!
            $endgroup$
            – Ben
            2 hours ago
















          3












          $begingroup$

          Assuming that the coefficient estimator $b$ is calculated by OLS estimation, you have:



          $$begin{equation} begin{aligned}
          b-beta
          &= (X'X)^{-1} X'y - beta \[6pt]
          &= (X'X)^{-1} X'(X beta + epsilon)- beta \[6pt]
          &= (X'X)^{-1} (X'X) beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= (X'X)^{-1} X' epsilon. \[6pt]
          end{aligned} end{equation}$$



          Presumably $e$ is the residual vector (different to the error vector $epsilon$) so we have $e = M_{[X]} Y = M_{[X]} epsilon$. Substituting this vector gives:



          $$begin{equation} begin{aligned}
          (b-beta) e'
          &= (X'X)^{-1} X' epsilon (M_{[X]} epsilon)' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}. \[6pt]
          end{aligned} end{equation}$$



          (The last step follows from the fact that $M_{[X]}$ is a symmetric matrix.) So the expression given by your professor is missing the $X'$ term.






          share|cite|improve this answer









          $endgroup$









          • 2




            $begingroup$
            Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
            $endgroup$
            – dlnB
            2 hours ago






          • 1




            $begingroup$
            @dlnb: Jinx! Buy me a coke!
            $endgroup$
            – Ben
            2 hours ago














          3












          3








          3





          $begingroup$

          Assuming that the coefficient estimator $b$ is calculated by OLS estimation, you have:



          $$begin{equation} begin{aligned}
          b-beta
          &= (X'X)^{-1} X'y - beta \[6pt]
          &= (X'X)^{-1} X'(X beta + epsilon)- beta \[6pt]
          &= (X'X)^{-1} (X'X) beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= (X'X)^{-1} X' epsilon. \[6pt]
          end{aligned} end{equation}$$



          Presumably $e$ is the residual vector (different to the error vector $epsilon$) so we have $e = M_{[X]} Y = M_{[X]} epsilon$. Substituting this vector gives:



          $$begin{equation} begin{aligned}
          (b-beta) e'
          &= (X'X)^{-1} X' epsilon (M_{[X]} epsilon)' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}. \[6pt]
          end{aligned} end{equation}$$



          (The last step follows from the fact that $M_{[X]}$ is a symmetric matrix.) So the expression given by your professor is missing the $X'$ term.






          share|cite|improve this answer









          $endgroup$



          Assuming that the coefficient estimator $b$ is calculated by OLS estimation, you have:



          $$begin{equation} begin{aligned}
          b-beta
          &= (X'X)^{-1} X'y - beta \[6pt]
          &= (X'X)^{-1} X'(X beta + epsilon)- beta \[6pt]
          &= (X'X)^{-1} (X'X) beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= beta + (X'X)^{-1} X' epsilon - beta \[6pt]
          &= (X'X)^{-1} X' epsilon. \[6pt]
          end{aligned} end{equation}$$



          Presumably $e$ is the residual vector (different to the error vector $epsilon$) so we have $e = M_{[X]} Y = M_{[X]} epsilon$. Substituting this vector gives:



          $$begin{equation} begin{aligned}
          (b-beta) e'
          &= (X'X)^{-1} X' epsilon (M_{[X]} epsilon)' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}' \[6pt]
          &= (X'X)^{-1} X' epsilon epsilon' M_{[X]}. \[6pt]
          end{aligned} end{equation}$$



          (The last step follows from the fact that $M_{[X]}$ is a symmetric matrix.) So the expression given by your professor is missing the $X'$ term.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered 2 hours ago









          BenBen

          26.8k230124




          26.8k230124








          • 2




            $begingroup$
            Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
            $endgroup$
            – dlnB
            2 hours ago






          • 1




            $begingroup$
            @dlnb: Jinx! Buy me a coke!
            $endgroup$
            – Ben
            2 hours ago














          • 2




            $begingroup$
            Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
            $endgroup$
            – dlnB
            2 hours ago






          • 1




            $begingroup$
            @dlnb: Jinx! Buy me a coke!
            $endgroup$
            – Ben
            2 hours ago








          2




          2




          $begingroup$
          Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
          $endgroup$
          – dlnB
          2 hours ago




          $begingroup$
          Nice, I think we both must have been typing our answers at the same time. I'm glad you also found the mistake.
          $endgroup$
          – dlnB
          2 hours ago




          1




          1




          $begingroup$
          @dlnb: Jinx! Buy me a coke!
          $endgroup$
          – Ben
          2 hours ago




          $begingroup$
          @dlnb: Jinx! Buy me a coke!
          $endgroup$
          – Ben
          2 hours ago


















          draft saved

          draft discarded




















































          Thanks for contributing an answer to Cross Validated!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          Use MathJax to format equations. MathJax reference.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstats.stackexchange.com%2fquestions%2f398797%2fwhy-does-this-expression-simplify-as-such%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          Anexo:Material bélico de la Fuerza Aérea de Chile Índice Aeronaves Defensa...

          Always On Availability groups resolving state after failover - Remote harden of transaction...

          update json value to null Announcing the arrival of Valued Associate #679: Cesar Manara ...