For formulas to show results, select them, press F2, and then press Enter. If the number of data points in array1 or array2 is less than 2, or if the variance of array1 or array2 is zero, F.TEST returns the #DIV/0! error value.Ĭopy the example data in the following table, and paste it in cell A1 of a new Excel worksheet. If an array or reference argument contains text, logical values, or empty cells, those values are ignored however, cells with the value zero are included. The arguments must be either numbers or names, arrays, or references that contain numbers. The first array or range of data.Īrray2 Required. The F.TEST function syntax has the following arguments:Īrray1 Required. For example, given test scores from public and private schools, you can test whether these schools have different levels of test score diversity. Use this function to determine whether two samples have different variances. As a rule of thumb, the smallest N should be around 30, but the larger the better.Returns the result of an F-test, the two-tailed probability that the variances in array1 and array2 are not significantly different. For example, an important assumption is that there is a large enough N, or number of participants in the sample. One could then say with confidence that the instructional intervention made the difference in having the posttest scores increase from the pretest scores.įinally, it is important to note that t tests, like most inferential statistics, are only robust if all the assumptions on which they are based are met. 05, you should "reject the null hypothesis" (recall that the null hypothesis is that both means are equal) and conclude that the means are, in fact, significantly different from one another. If the probability value shown by the calculator for a two-tailed test is less than. For a correlated t test, the degrees of freedom is always N-1 (number of participants minus one). You will need to enter your t value along with the degrees of freedom (df) of your sample. But, here is a nice web site that will compute the probability value for you: Traditionally, to do this, one would look up the value on a t distribution table. 05, meaning 95 times out of a 100, the differences would not be due to chance). Determining if you should reject the null hypothesis based on the t valueĪfter you compute the t statistic, you will need to determine whether the difference between the means is statistically significant based on a predetermined probability (usually. OK, here is a second version of the t test that is much easier to compute:Īnd, here is the formula for computing the standard deviation of the distribution of differences between the scores:Īs you can see, this formula uses the sums of the differences between each person's pretest and posttest score. That is important because it shows that this statistic is based on computing a correlation between the two means. But, before we explore this easier way, notice that this term uses r, which is a correlation coefficient. To find the p-value for this test statistic, we will use the following formula in Excel: T.DIST (. Fortunately, there is an easier way to do the computation. "S sub d bar") between the correlated means is rather daunting. However, as you can see, computing the standard error of the difference (i.e. The first is the standard formula for computing the t test: Consult these formulas often as you complete the activity. You will use two formulas in this activity. I hope you will enjoy this activity and find it relevant and satisfying. Click on the following link to launch the video in a new window: The video is approximately 18 minutes in length. When finished, email your Excel file as an attachment to Lloyd Rieber at with the subject line: "yourLastName - Statistics Activity 2." Follow the video instructions carefully as you work with Excel. Lloyd Rieber has prepared a video tutorial for you. Save this updated Excel file as "yourLastName-statistics2.xls" (e.g.
You will use the Excel spreadsheet file that you created in the previous activity.
TEST STATISTIC FORMULA EXCEL PLUS
In this activity, you will compute the t statistic using the data set used in the previous activity as the pretest plus a set of posttest scores that will be emailed to you. This can be found on your course learning plan. View Lloyd Rieber's pre-recorded presentation of an instruction to quantitative research methods, corresponding to chapters 8-11 of the 10th edition of the Leedy and Ormrod textbook.
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