The following is a description of the fields in this report: Figure 3 displays the principal output of this tool for the data in Example 1.įigure 3 – Output from Regression data analysis tool The creation of a regression line and hypothesis testing of the type described in this section can be carried out using this tool. R Square is the correlation of determination r 2 (see Definition 2 of Basic Concepts of Correlation), while all the other values are as described above with the exception of the standard error of the y-intercept, which will be explained shortly.Įxcel also provides a Regression data analysis tool. I have added the appropriate labels manually for clarity.įigure 2 – LINEST(B4:B18,A4:A18,TRUE,TRUE) output
To make all of this clearer, Figure 2 displays the output from LINEST(A4:A18, B4:B18, TRUE, TRUE) using the data in Figure 1. The LINEST function returns a number of values, but unfortunately no labels for these values. To use LINEST, begin by highlighting a blank 5 × 2 region, enter =LINEST( and then highlight the R1 array, enter a comma, highlight the R2 array and finally enter ,TRUE,TRUE) and press Ctrl-Shft-Enter. LINEST(R1, R2, TRUE, TRUE) – an array function that generates a number of useful statistics. STEYX(R1, R2) = standard error of the estimate s y∙x = SQRT( MS Res) This would be useful for example when testing whether the slope of the regression line for the population of men in Example 1 is significantly different from that of women.Ĭlick here for additional information and an example about Hypothesis Testing for Comparing the Slopes of Two Independent Samples.Įxcel Functions: where R1 = the array of observed values and R2 = the array of observed values. Observation: We can also test whether the slopes of the regression lines arising from two independent populations are significantly different. Note that the 95% confidence interval for the population slope isī ± t crit
0028 2.16 = t crit) we reject the null hypothesis, and so we can’t conclude that the population slope is zero. the slope of the population regression line is zero):Įxample 1: Test whether the slope of the regression line in Example 1 of Method of Least Squares is zero.įigure 1 shows the worksheet for testing the null hypothesis that the slope of the regression line is 0.įigure 1 – t- test of the slope of the regression line Thus Theorem 1 of One Sample Hypothesis Testing for Correlation can be transformed into the following test of the hypothesis H 0: β = 0 (i.e. It follows that ρ = 0 if and only if β = 0. Since by the population version of Property 1 of Method of Least Squares Putting these elements together we get that Observation: By Theorem 1 of One Sample Hypothesis Testing for Correlation, under certain conditions, the test statistic t has the propertyīut by Property 1 of Method of Least SquaresĪnd by Definition 3 of Regression Analysis and Property 4 of Regression Analysis
#HOW TO USE EVIEWS 10 TO RUN A REGRESSION HOW TO#
We now show how to test the value of the slope of the regression line.
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