WEBVTT 00:00:00.000 --> 00:00:01.500 align:middle line:90% [MUSIC PLAYING] 00:00:01.500 --> 00:00:16.000 align:middle line:90% 00:00:16.000 --> 00:00:18.190 align:middle line:84% Hello and welcome to a brief tutorial 00:00:18.190 --> 00:00:21.700 align:middle line:84% on running a one-way ANOVA using JASP. 00:00:21.700 --> 00:00:24.110 align:middle line:84% So we have the textbook example over here. 00:00:24.110 --> 00:00:26.590 align:middle line:84% And the goal of this was to see how long it took people 00:00:26.590 --> 00:00:28.189 align:middle line:90% to complete a short quiz. 00:00:28.189 --> 00:00:30.230 align:middle line:84% And we put them in three different colored rooms. 00:00:30.230 --> 00:00:33.864 align:middle line:84% We had a white room, a yellow room, and a blue room. 00:00:33.864 --> 00:00:36.280 align:middle line:84% And you can see these, again, to see what the numbers were 00:00:36.280 --> 00:00:37.930 align:middle line:90% that we associated with those-- 00:00:37.930 --> 00:00:42.070 align:middle line:84% 1 was white, 2 was yellow, and 3 was blue. 00:00:42.070 --> 00:00:44.625 align:middle line:84% And then, of course, we have over here, the time in minutes. 00:00:44.625 --> 00:00:46.884 align:middle line:84% So let's go ahead and calculate a one-way ANOVA. 00:00:46.884 --> 00:00:49.300 align:middle line:84% To do this, I'm going to click over here on the ANOVA tab, 00:00:49.300 --> 00:00:51.670 align:middle line:90% and I'm going to click on ANOVA. 00:00:51.670 --> 00:00:55.240 align:middle line:84% From there, what I need to do is I need to take my fixed factor. 00:00:55.240 --> 00:00:56.861 align:middle line:84% In this case, you'll notice down here 00:00:56.861 --> 00:00:58.360 align:middle line:84% it's going to be one of these types. 00:00:58.360 --> 00:00:59.780 align:middle line:84% And of course, we know that it's nominal, 00:00:59.780 --> 00:01:01.480 align:middle line:84% so we're going to click that one over. 00:01:01.480 --> 00:01:02.950 align:middle line:84% And then our dependent variable is 00:01:02.950 --> 00:01:04.575 align:middle line:84% going to be an interval ratio variable, 00:01:04.575 --> 00:01:06.190 align:middle line:84% so I'm going to click that over there. 00:01:06.190 --> 00:01:08.569 align:middle line:84% So it's immediately going to give you your ANOVA. 00:01:08.569 --> 00:01:10.985 align:middle line:84% And let us know-- right here, you can see that the degrees 00:01:10.985 --> 00:01:19.750 align:middle line:84% of freedom is 2, F is 7.20, and p is equal to 0.014. 00:01:19.750 --> 00:01:21.490 align:middle line:84% So we know that the overall model 00:01:21.490 --> 00:01:23.530 align:middle line:90% is statistically significant. 00:01:23.530 --> 00:01:25.540 align:middle line:84% But it doesn't tell us everything. 00:01:25.540 --> 00:01:29.329 align:middle line:84% So a few more things that we would probably want to look at. 00:01:29.329 --> 00:01:31.870 align:middle line:84% One, we're definitely going to want to run the post-hoc test. 00:01:31.870 --> 00:01:33.661 align:middle line:84% So I'm going to go ahead and click on that, 00:01:33.661 --> 00:01:35.500 align:middle line:84% and I want to shift that over here. 00:01:35.500 --> 00:01:38.080 align:middle line:84% And it's immediately going to pull it up. 00:01:38.080 --> 00:01:41.200 align:middle line:84% I'm going to go ahead and run Scheffé instead of Tukey. 00:01:41.200 --> 00:01:42.700 align:middle line:84% It's a little bit more conservative, 00:01:42.700 --> 00:01:44.616 align:middle line:84% but I think, generally, for what we're looking 00:01:44.616 --> 00:01:47.060 align:middle line:90% for, it's somewhat useful. 00:01:47.060 --> 00:01:48.550 align:middle line:84% We also could run, down here, you 00:01:48.550 --> 00:01:51.010 align:middle line:90% could look at Descriptive Plots. 00:01:51.010 --> 00:01:53.460 align:middle line:84% You could look at some additional items. 00:01:53.460 --> 00:01:56.170 align:middle line:84% One that we would want is this one 00:01:56.170 --> 00:01:58.480 align:middle line:84% so we could see our descriptive statistics. 00:01:58.480 --> 00:02:01.090 align:middle line:84% It's also where we're going to get our effect size, 00:02:01.090 --> 00:02:03.560 align:middle line:90% so that we can see eta-squared. 00:02:03.560 --> 00:02:08.710 align:middle line:84% So let's look at what we have here as a whole. 00:02:08.710 --> 00:02:11.170 align:middle line:84% So one of the first things you're going to see here 00:02:11.170 --> 00:02:14.380 align:middle line:84% is we have the means for the three different groups. 00:02:14.380 --> 00:02:16.870 align:middle line:90% It has our confidence intervals. 00:02:16.870 --> 00:02:21.010 align:middle line:84% It also, way up here, you're going to now see 00:02:21.010 --> 00:02:25.060 align:middle line:90% eta is listed at 0.615. 00:02:25.060 --> 00:02:28.000 align:middle line:84% So that is how all of this gets reported. 00:02:28.000 --> 00:02:29.500 align:middle line:84% The one that we want to look at now, 00:02:29.500 --> 00:02:31.180 align:middle line:84% though, is this little box right here, 00:02:31.180 --> 00:02:33.380 align:middle line:90% which is the Post Hoc Analysis. 00:02:33.380 --> 00:02:37.030 align:middle line:84% Now, one of the things that they do with the post-hoc analysis 00:02:37.030 --> 00:02:39.130 align:middle line:84% here is it doesn't necessarily show us, 00:02:39.130 --> 00:02:42.070 align:middle line:84% it doesn't flag, which colors are different from which. 00:02:42.070 --> 00:02:44.036 align:middle line:84% So let's go ahead and look at this. 00:02:44.036 --> 00:02:45.910 align:middle line:84% So it's going to give us our first one, which 00:02:45.910 --> 00:02:47.890 align:middle line:84% is the white room versus the yellow room. 00:02:47.890 --> 00:02:49.780 align:middle line:84% And if we come over here, we can look. 00:02:49.780 --> 00:02:52.550 align:middle line:90% There is the p-value at 0.22. 00:02:52.550 --> 00:02:55.670 align:middle line:84% So we know that one is not statistically significant. 00:02:55.670 --> 00:02:58.060 align:middle line:84% So there is no difference between the white room 00:02:58.060 --> 00:02:59.024 align:middle line:90% and the yellow room. 00:02:59.024 --> 00:03:01.315 align:middle line:84% Next, we can look at the white room with the blue room. 00:03:01.315 --> 00:03:03.340 align:middle line:84% And we're going to scroll all the way over, 00:03:03.340 --> 00:03:09.310 align:middle line:84% and there is a statistical difference there at 0.014. 00:03:09.310 --> 00:03:12.040 align:middle line:84% So there is a statistically significant difference 00:03:12.040 --> 00:03:16.030 align:middle line:84% in how long it took students to complete the quiz between those 00:03:16.030 --> 00:03:18.520 align:middle line:84% who are in the white room and those in the blue room. 00:03:18.520 --> 00:03:20.290 align:middle line:84% And our last comparison is students 00:03:20.290 --> 00:03:22.550 align:middle line:84% that were in the yellow room compared to the blue. 00:03:22.550 --> 00:03:23.770 align:middle line:84% And if we scroll all the way over, 00:03:23.770 --> 00:03:25.186 align:middle line:84% once again, you're going to notice 00:03:25.186 --> 00:03:28.210 align:middle line:84% that there is no statistically significant difference 00:03:28.210 --> 00:03:29.272 align:middle line:90% between those. 00:03:29.272 --> 00:03:30.730 align:middle line:84% So the only difference we found was 00:03:30.730 --> 00:03:32.225 align:middle line:84% between students who were taking it 00:03:32.225 --> 00:03:34.920 align:middle line:90% in the white and the blue room. 00:03:34.920 --> 00:03:37.410 align:middle line:84% And so that's all that it takes to run 00:03:37.410 --> 00:03:39.520 align:middle line:90% a one-way ANOVA using JASP. 00:03:39.520 --> 00:03:41.670 align:middle line:90% [MUSIC PLAYING] 00:03:41.670 --> 00:03:53.916 align:middle line:90%