standard error microsoft excel data analysis regression

Let us say we have a dataset of some individuals with their age, bio-mass index (BMI), and the amount spent by them on medical expenses in a month. t a = 1,75, so | t a > t crit, consequently, the regression coefficient %is significant under the probability 10% by the given linear regression model.You can download this Linear Regression Excel Template here – Linear Regression Excel Template Method #1 – Scatter Chart with a Trendline t a = -3,22, so | fc a |> t crit, consequently, the regression coefficient %is significant under the probability 10% by the given linear regression model. t a2 = 1,75, so | t (l21 t crit, consequently, the regression coefficient a 0 is significant under the probability 10% by the given linear regression model. t a± = -3,22, so | t ai|> t crit, consequently, the regression coefficient a^s significant under the probability 5% by the given linear regression model. As t ao =2,93 | t a(| |> t crit, consequently, the regression coefficient a 0 is significant under the probability 5% by the given linear regression model. To calculate t crit, in Excel we should use the statistics fonnula CTbIOH P A C110BP with probability of 5%, df=number of observations (in our case 33)-number of estimated parameters (in our case 3)=30. To check this inequality it is needed to take t from the Table 3 (regression analysis). If the inequality is right, the coefficients are significant.

It is needed to check the following inequality: F crit t crit, where t is the value of t-statistics. The meaning of it is that selected factors do not effect significantly the given model. It can said that such value of the R is not good, because it is close to 0 (maximum R = 1). Value of the multiple coefficient of detennination R equals to 0,46 shows that 46 % of total deviation of GDP is explained by the variation of bank rate and total investment. Let me consider R -test, F-test, t-test, Goldfeld-Quant test and Durbin-Watson test. TestingĪnother step of the analysis is model testing. Residual values are calculated as the difference between empirical y and theoretical y (see in the application 2). Table 5 contains theoretical values y t, computed with the help of regression formula, and residual values. In the square brackets there are the value of t-statistic, which is in the Table 4. All the information in the round brackets is obtained from the Table 4. Where a 0 = 1761,06 with the standard error of 600,47 (in the round brackets), a ±=-87,84 with the standard error of 27,28 (in the round brackets), a 2= 45,22 with the standard error of 25,81 (in the round brackets), the standard error of the disturbance term is 266,8 (in the round brackets).

Standard error microsoft excel data analysis regression