Equation For Standard Error Of Regression Coefficient

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Standard Error Of Regression Coefficient Calculator

works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top How to derive the standard error of linear regression coefficient up vote 2 down vote favorite 3 For this univariate linear regression model $$y_i = \beta_0 + \beta_1x_i+\epsilon_i$$ given data set $D=\{(x_1,y_1),...,(x_n,y_n)\}$, the coefficient estimates are $$\hat\beta_1=\frac{\sum_ix_iy_i-n\bar x\bar y}{n\bar x^2-\sum_ix_i^2}$$ $$\hat\beta_0=\bar y - \hat\beta_1\bar x$$ standard error of regression coefficient excel Here is my question, according to the book and Wikipedia, the standard error of $\hat\beta_1$ is $$s_{\hat\beta_1}=\sqrt{\frac{\sum_i\hat\epsilon_i^2}{(n-2)\sum_i(x_i-\bar x)^2}}$$ How and why? standard-error inferential-statistics share|improve this question edited Mar 6 '15 at 14:38 Christoph Hanck 9,17332149 asked Feb 9 '14 at 9:11 loganecolss 5531926 stats.stackexchange.com/questions/44838/… –ocram Feb 9 '14 at 9:14 @ocram, thanks, but I'm not quite capable of handling matrix stuff, I'll try. –loganecolss Feb 9 '14 at 9:20 1 @ocram, I've already understand how it comes. But still a question: in my post, the standard error has $(n-2)$, where according to your answer, it doesn't, why? –loganecolss Feb 9 '14 at 9:40 add a comment| 1 Answer 1 active oldest votes up vote 7 down vote accepted 3rd comment above: I've already understand how it comes. But still a question: in my post, the standard error has (n−2), where according to your answer, it doesn't, why? In my post, it is found that $$ \widehat{\text{se}}(\hat{b}) = \sqrt{\frac{n \hat{\sigma}^2}{n\sum x_i^2 - (\sum x_i)^2}}. $$ The denominator can be written as $$ n \sum_i (x_i - \bar{x})^2 $$ Thus, $$ \widehat{\text{se}}(\hat{b}) = \sqrt{\frac{\hat{\sigma}^2}{\sum_i (x_i - \bar{x})^2}} $$ With $$ \ha

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Confidence Interval Regression Coefficient

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Variance Regression Coefficient

AP practice exam Problems and solutions Formulas Notation Share with Friends Regression Slope: Confidence Interval This lesson describes how to construct a confidence interval around the slope http://stats.stackexchange.com/questions/85943/how-to-derive-the-standard-error-of-linear-regression-coefficient of a regression line. We focus on the equation for simple linear regression, which is: ŷ = b0 + b1x where b0 is a constant, b1 is the slope (also called the regression coefficient), x is the value of the independent variable, and ŷ is the predicted value of the dependent variable. Estimation Requirements The approach described http://stattrek.com/regression/slope-confidence-interval.aspx?Tutorial=AP in this lesson is valid whenever the standard requirements for simple linear regression are met. The dependent variable Y has a linear relationship to the independent variable X. For each value of X, the probability distribution of Y has the same standard deviation σ. For any given value of X, The Y values are independent. The Y values are roughly normally distributed (i.e., symmetric and unimodal). A little skewness is ok if the sample size is large. Previously, we described how to verify that regression requirements are met. The Variability of the Slope Estimate To construct a confidence interval for the slope of the regression line, we need to know the standard error of the sampling distribution of the slope. Many statistical software packages and some graphing calculators provide the standard error of the slope as a regression analysis output. The table below shows hypothetical output for the following regression equation: y = 76 + 35x . Predictor Coef SE Coef T P Constant 76 30 2.53 0.01 X

Curve) Z-table (Right of Curve) Probability and Statistics Statistics Basics Probability Regression Analysis Critical Values, Z-Tables & Hypothesis Testing Normal Distributions: Definition, Word Problems T-Distribution Non Normal Distribution Chi Square Design of Experiments Multivariate Analysis http://www.statisticshowto.com/find-standard-error-regression-slope/ Sampling in Statistics Famous Mathematicians and Statisticians Calculators Variance and Standard Deviation Calculator Tdist Calculator Permutation Calculator / Combination Calculator Interquartile Range Calculator Linear Regression Calculator Expected Value Calculator Binomial Distribution Calculator Statistics Blog Calculus Matrices Practically Cheating Statistics Handbook Navigation Standard Error of Regression Slope Probability and Statistics > Regression Analysis > Standard Error of Regression Slope Standard Error of Regression Slope: Overview Standard errors for regression are measures of regression coefficient how spread out your y variables are around the mean, μ.The standard error of the regression slope, s (also called the standard error of estimate) represents the average distance that your observed values deviate from the regression line. The smaller the "s" value, the closer your values are to the regression line. Standard error of regression slope is a term you're likely to come across in AP Statistics. In fact, standard error of you'll find the formula on the AP statistics formulas list given to you on the day of the exam. Standard Error of Regression Slope Formula SE of regression slope = sb1 = sqrt [ Σ(yi - ŷi)2 / (n - 2) ] / sqrt [ Σ(xi - x)2 ]). The equation looks a little ugly, but the secret is you won't need to work the formula by hand on the test. Even if you think you know how to use the formula, it's so time-consuming to work that you'll waste about 20-30 minutes on one question if you try to do the calculations by hand! The TI-83 calculator is allowed in the test and it can help you find the standard error of regression slope. Note: The TI83 doesn't find the SE of the regression slope directly; the "s" reported on the output is the SE of the residuals, not the SE of the regression slope. However, you can use the output to find it with a simple division. Step 1: Enter your data into lists L1 and L2. If you don't know how to enter data into a list, see:TI-83 Scatter Plot.) Step 2: Press STAT, scroll right to TESTS and then select E:LinRegTTest Step 3: Type in t