Question 35 Not yet answered Points out of 5.00 A hypothesis...

Question 35 Not yet answered Points out of 5.00 A hypothesis test produces a t statistic of t = 2.10. If the researcher is using a two-tailed test with ? = .05, how large does the sample have to be in order to reject the null hypothesis? Select one: a. At least n = 12 b. At least n = 11 c. At least n = 20 d. At least n = 21 Question 36 Not yet answered Points out of 5.00 In a two-factor ANOVA, MS within treatments = ______. a. MSeffect / MSA within treatments b. MSbetween treatments / MSerror c. SSAbetween treatments - SSA - SSB

Transcript

00:01 So we're told that a hypothesis test produced a t -statistic of 2 .10, and the researcher is using a two -tailed test where the alpha is 0 .05.

00:22 And what that means is we're taking this alpha and splitting it in two tails.

00:24 So it's a t -distribution, so like this, and our t -score of zero is right in the center.

00:31 We found 2 .10.

00:34 So we find this area here, but because we're doing a two -tailed test, we need to double it.

00:40 We need to assume that it could have been below this value as well, negative 2 .10.

00:46 So the p -value is the sum of these two areas, and then the rule is to reject the hypothesis.

00:52 If our p -value is less than this value, then the alpha is 0 .05.

01:00 So the question is, how large a sample does it have to be to reject the hypothesis? because the t -distribution depends upon the sample size, so we want to find the n, such that we get a p -value here that's less than 0 .05.

01:14 So we have the n of, we have 11, 12, 20, and 21.

01:19 But we need not just the sample size, well, we need the sample size, but the question is about, in order to get the p -value, we need the degrees of freedom.

01:28 And the degrees of freedom are found by taking the sample size minus 1.

01:31 So the degrees of freedom are what we need to use here.

01:36 And we're going to use the spreadsheet function based on this, the degrees of freedom.

01:40 So we have, in this case, it's going to be 10.

01:44 This is going to be 11.

01:46 This is going to be 19.

01:48 Df, this is going to be 20.

01:54 So let me show you the values we get and the functions we use to get them.

02:00 So here we go.

02:00 So these are the p -values right here.

02:11 And what we have here, we use the t -dist function.

02:15 This is an excel spreadsheet, google sheets, lots of ways you can find these.

02:19 But what you do, you look up, you put in the test statistic, the t -statistic here...

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