The observed difference between the sample means (33 - 24.8) is not convincing enough to say that the average number of study hours between female and male students differ significantly. Therefore, we do not reject the null hypothesis. lf t Stat t Critical two-tail, we reject the null hypothesis. Click in the Output Range box and select cell E1.Ĭonclusion: We do a two-tail test (inequality). Click in the Hypothesized Mean Difference box and type 0 (H 0: μ 1 - μ 2 = 0).ħ. x is the value at which the distribution is. Here 2 F 1 is the hypergeometric function. Let's understand the cumulative distribution function for the t distribution with different degrees of freedom. The T distribution function varies with degrees of freedom. Click in the Variable 2 Range box and select the range B2:B6.Ħ. T distribution is a bell shaped curve but much flatter than normal distribution curve. We may easily generate n number of random. The rt () function generates random deviates of the t -distribution and is written as rt (n, df). Apply the help () function on these functions for further information. Click in the Variable 1 Range box and select the range A2:A7.ĥ. The R software provides access to the t -distribution by the dt (), pt (), qt () and rt () functions. Select t-Test: Two-Sample Assuming Unequal Variances and click OK.Ĥ. Note: can't find the Data Analysis button? Click here to load the Analysis ToolPak add-in.ģ. On the Data tab, in the Analysis group, click Data Analysis. First, perform an F-Test to determine if the variances of the two populations are equal. To perform a t-Test, execute the following steps.ġ.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |