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    p-value of a coefficient from a regression




    The t-stat value follows a two-tail symmetric t-distribution with mean and median of zero?

    Am I correct so far?

    If so, then how can you get a p-value > .5 if the t-stat is greater than 0?

    What does a p-value of .89 mean? Wouldn't that mean the t-stat is way negative and is to the other end of the tail?

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    Re: p-value of a coefficient from a regression

    Not following, may help if you provide your example. The p-value is the probability of getting a value (parameter) that extreme given that there really exist not relationship. Are you talking about your t-statics or p-values? T-statistic is the difference over the standard error, which is the number of standard deviations the groups differs from the other group. So typically if it is around 2 standard deviation different in either direction, we say the probability is low for that extreme of a difference under the pretenses that the two groups are equal.
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    Re: p-value of a coefficient from a regression

    Have you learned about two-sided tests?
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    Re: p-value of a coefficient from a regression

    Oahz, I think you are confusing the relationship between the t-statistic and p-value.
    I think visuals can help understand distributions and p-values, so to build on hlsmith answer, here are a few links:
    Even though this article is based on the premises that you are using minitab (a stats program) - the basic theory is there: http://blog.minitab.com/blog/statist...-in-statistics.

    Here is a video series that may help also: https://www.khanacademy.org/math/pro...g-and-p-values

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    Re: p-value of a coefficient from a regression

    I think might have figured it out. Tell me if I'm correct.

    My question was, how is the p-value for an estimated coefficient derived?

    Answer:

    If you get a positive t-stat of, say t, and t corresponds to a probability, say p*, of randomly getting t or a value greater than t from the t-distribution, then the p-value is equal to 2p*.

    Conversely,

    If you get a negative t-stat of, say t, and t corresponds to a probability, say p*, of randomly getting t or a value less than t from the t-distribution, then the p-value is equal to 2P*.

    Am I correct?

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    Re: p-value of a coefficient from a regression

    Are you examining a simple linear regression model? If you tell us about the model we can provide more and better information.
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    Re: p-value of a coefficient from a regression

    It is linear, but it there could be multiple explanatory variables.

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    Re: p-value of a coefficient from a regression

    You are testing whether the variable has a slope equal to zero.


    It is taking the slope value (coefficient) for the variable and dividing it by the standard error (sampling variation) and that provides the t-statics. Can be negative or positive, just like the slope. Now it interprets the value based on the degrees of freedom using the t-distribution. If the t-statistic is large or small enough then it would have a low probability of occurring given that the slope is really zero (null hypothesis).
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    Re: p-value of a coefficient from a regression

    Quote Originally Posted by hlsmith View Post
    You are testing whether the variable has a slope equal to zero.


    It is taking the slope value (coefficient) for the variable and dividing it by the standard error (sampling variation) and that provides the t-statics. Can be negative or positive, just like the slope. Now it interprets the value based on the degrees of freedom using the t-distribution. If the t-statistic is large or small enough then it would have a low probability of occurring given that the slope is really zero (null hypothesis).
    I understand that much.

    My confusion is the p-value.

    Just answer this one question: can you have p-value of greater than .5 if the t-statistic is greater than 0?

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    Re: p-value of a coefficient from a regression


    I don't have emotions and sometimes that makes me very sad.

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