Note that the Other Counties Data has been placed In Variable 1 (left) location to match its location in the Alternative Hypothesis.The output from the tools can be a bit confusing because, unlike other statistical software, these do not allow you to specify the tail of the test before you run the analysis.
Two-Sample Assuming Unequal Variances On Excel How To Interpret TheHere is how Microsoft explains how to interpret the output here.For convenience, I am just using the output from the t-test: Two-Sample Assuming Unequal Variances, but the concepts apply to all three t-test tools. Traditionally, the county bridges between urban and rural Alabama communities. But in more recent times, Montgomery county has been classified as a metro county. The Montgomery mayor thinks the obesity prevalence in Montgomery County is significantly different from the average obesity prevalence in the other Alabama counties. Note: The sample data is from the National Health Interview Survey (About the National Health Interview Survey, 2019). This will help you keep things straight and make interpreting the results easier. The Other Counties group (red highlight) is on the right side of the Null equation and must be in the Variable 2 Range field. ![]() But here our t Stat of 1.867 does not fall in either rejection area, so we must decide to not reject the Null. Thankfully, for a two-tail test, we can always just use the two-tail p-value the Excel tool gives us. It is 0.066 which is larger than our significance level, alpha, of 0.05. Thus, this rule also tells us to not reject the Null that there is no difference in the ratings. Why not just run the two-tail As you will see, a one-tail test gives us more power to detect a real effect that is there in the direction we believe it to have. The downside of a one-tail test, if you guess wrong and the effect is in the other direction, the test has no power to detect it. Remember the less than symbol points to the left, so this is a left-tail test. For a left-tail test, we need the negative t Critical one-tail which is -1.669. You should note that the one-tail critical value is smaller than the two-tail value of -1.997 because we put all of the alpha in that one tail which pushes the critical value toward the mean. If the t Stat is positive, the Excel one-tail p-value is for the right tail the probability of getting a positive value for t-stat that is as large or even larger. You should also notice that the one-tail p-value is exactly half of the two-tail p-value. So, the left-tail p-value is 1 0.0332 0.9676. That is much larger than 0.05, so this method tells us to not reject the Null. Here, the Alternative math operator is greater than which points to the right, so this is a right-tail test. We use the positive one-tail critical value of 1.669 and we find our t Stat of -1.866 is very far away from the right tail rejection area. To find the right-side p-value, we must recall that the area under the curve is equal to 1. We want the right-tail p-value, so we must subtract that left-tail value from 1 to get the right-tail p-value.
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