WEBVTT 00:00:00.500 --> 00:00:02.620 It never hurts to get a bit more practice. 00:00:02.620 --> 00:00:05.600 So this is problem number five from the normal distribution 00:00:05.600 --> 00:00:11.560 chapter from ck12.org's AP statistics FlexBook. 00:00:11.560 --> 00:00:16.030 So they're saying, the 2007 AP statistics examination scores 00:00:16.030 --> 00:00:20.750 were not normally distributed with a mean of 2.8 00:00:20.750 --> 00:00:23.964 and a standard deviation of 1.34. 00:00:23.964 --> 00:00:25.630 They cite some College Board stuff here. 00:00:25.630 --> 00:00:27.170 I didn't copy and paste that. 00:00:27.170 --> 00:00:29.170 What is the approximate z-score? 00:00:29.170 --> 00:00:31.530 Remember, z-score is just how many 00:00:31.530 --> 00:00:33.980 standard deviations you are away from the mean. 00:00:33.980 --> 00:00:35.950 What is the approximate z-score that 00:00:35.950 --> 00:00:39.337 corresponds to an exam score of 5? 00:00:39.337 --> 00:00:40.920 So we really just have to figure out-- 00:00:40.920 --> 00:00:42.628 this is a pretty straightforward problem. 00:00:42.628 --> 00:00:45.720 We just need to figure out how many standard deviations is 00:00:45.720 --> 00:00:48.340 5 from the mean? 00:00:48.340 --> 00:00:53.370 Well, you just take 5 minus 2.8, right? 00:00:53.370 --> 00:00:54.400 The mean is 2.8. 00:00:54.400 --> 00:00:56.121 Let me be very clear, mean is 2.8. 00:00:56.121 --> 00:00:56.870 They give us that. 00:00:56.870 --> 00:00:58.800 Didn't even have to calculate it. 00:00:58.800 --> 00:01:00.230 So the mean is 2.8. 00:01:00.230 --> 00:01:03.760 So 5 minus 2.8 is equal to 2.2. 00:01:03.760 --> 00:01:06.374 So we're 2.2 above the mean. 00:01:06.374 --> 00:01:08.540 And if we want that in terms of standard deviations, 00:01:08.540 --> 00:01:10.770 we just divide by our standard deviation. 00:01:10.770 --> 00:01:14.860 You divide by 1.34. 00:01:14.860 --> 00:01:17.290 Divide by 1.34. 00:01:17.290 --> 00:01:20.710 I'll take out the calculator for this. 00:01:20.710 --> 00:01:31.280 So we have 2.2 divided by 1.34 is equal to 1.64. 00:01:31.280 --> 00:01:34.966 So this is equal to 1.64. 00:01:34.966 --> 00:01:37.590 And that's choice C. So this was actually very straightforward. 00:01:37.590 --> 00:01:40.620 We just have to see how far away we are from the mean 00:01:40.620 --> 00:01:42.929 if we get a score of 5-- which hopefully you 00:01:42.929 --> 00:01:44.720 will get if you're taking the AP statistics 00:01:44.720 --> 00:01:46.242 exam after watching these videos. 00:01:46.242 --> 00:01:48.450 And then you divide by the standard deviation to say, 00:01:48.450 --> 00:01:50.850 how many standard deviations away from the mean 00:01:50.850 --> 00:01:52.230 is the score of 5? 00:01:52.230 --> 00:01:53.545 It's 1.64. 00:01:53.545 --> 00:01:55.670 I think the only tricky thing here might have been, 00:01:55.670 --> 00:01:58.400 you might have been tempted to pick choice E, which says, 00:01:58.400 --> 00:02:01.300 the z-score cannot be calculated because the distribution is not 00:02:01.300 --> 00:02:01.800 normal. 00:02:01.800 --> 00:02:04.700 And I think the reason why you might have had that temptation 00:02:04.700 --> 00:02:07.430 is because we've been using z-scores 00:02:07.430 --> 00:02:10.300 within the context of a normal distribution. 00:02:10.300 --> 00:02:12.860 But a z-score literally just means how many 00:02:12.860 --> 00:02:15.950 standard deviations you are away from the mean. 00:02:15.950 --> 00:02:18.290 It could apply to any distribution 00:02:18.290 --> 00:02:21.820 that you could calculate a mean and a standard deviation for. 00:02:21.820 --> 00:02:23.910 So E is not the correct answer. 00:02:23.910 --> 00:02:27.045 A z-score can apply to a non-normal distribution. 00:02:27.045 --> 00:02:29.170 So the answer is C. And I guess that's a good point 00:02:29.170 --> 00:02:31.094 of clarification to get out of the way. 00:02:31.094 --> 00:02:33.260 And I thought I would do two problems in this video, 00:02:33.260 --> 00:02:35.460 just because that one was pretty short. 00:02:35.460 --> 00:02:36.900 So problem number six. 00:02:36.900 --> 00:02:39.350 The height of fifth grade boys in the United States 00:02:39.350 --> 00:02:41.480 is approximately normally distributed-- 00:02:41.480 --> 00:02:45.690 that's good to know-- with a mean height of 143.5 00:02:45.690 --> 00:02:46.410 centimeters. 00:02:46.410 --> 00:02:50.960 So it's a mean of 143.5 centimeters 00:02:50.960 --> 00:02:56.635 and a standard deviation of about 7.1 centimeters. 00:03:01.700 --> 00:03:04.620 What is the probability that a randomly chosen fifth grade 00:03:04.620 --> 00:03:09.134 boy would be taller than 157.7 centimeters? 00:03:09.134 --> 00:03:10.800 So let's just draw out this distribution 00:03:10.800 --> 00:03:13.755 like we've done in a bunch of problems so far. 00:03:13.755 --> 00:03:15.600 They're just asking us one question, 00:03:15.600 --> 00:03:19.320 so we can mark this distribution up a good bit. 00:03:19.320 --> 00:03:21.410 Let's say that's our distribution. 00:03:21.410 --> 00:03:28.270 And the mean here, the mean they told us is 143.5. 00:03:28.270 --> 00:03:30.414 They're asking us taller than 157.7. 00:03:30.414 --> 00:03:32.080 So we're going in the upwards direction. 00:03:32.080 --> 00:03:35.360 So one standard deviation above the mean 00:03:35.360 --> 00:03:37.740 will take us right there. 00:03:37.740 --> 00:03:40.510 And we just have to add 7.1 to this number right here. 00:03:40.510 --> 00:03:42.700 We're going up by 7.1. 00:03:42.700 --> 00:03:45.980 So 143.5 plus 7.1 is what? 00:03:45.980 --> 00:03:49.440 150.6. 00:03:49.440 --> 00:03:51.047 That's one standard deviation. 00:03:51.047 --> 00:03:52.880 If we were to go another standard deviation, 00:03:52.880 --> 00:03:54.950 we'd go 7.1 more. 00:03:54.950 --> 00:03:57.500 What's 7.1 plus 150.6? 00:03:57.500 --> 00:04:02.950 It's 157.7, which just happens to be 00:04:02.950 --> 00:04:04.220 the exact number they ask for. 00:04:04.220 --> 00:04:06.240 They're asking for the probability 00:04:06.240 --> 00:04:08.304 of getting a height higher than that. 00:04:08.304 --> 00:04:10.470 So they want to know, what's the probability that we 00:04:10.470 --> 00:04:12.830 fall under this area right here? 00:04:12.830 --> 00:04:15.980 Or essentially more than two standard deviations 00:04:15.980 --> 00:04:16.630 from the mean. 00:04:16.630 --> 00:04:18.670 Or above two standard deviations. 00:04:18.670 --> 00:04:21.420 We can't count this left tail right there. 00:04:21.420 --> 00:04:24.480 So we can use the empirical rule. 00:04:24.480 --> 00:04:26.630 If we do our standard deviations to the left, 00:04:26.630 --> 00:04:29.830 that's one standard deviation, two standard deviations. 00:04:29.830 --> 00:04:32.010 We know what this whole area is. 00:04:32.010 --> 00:04:35.660 Let me pick a different color so that I don't. 00:04:35.660 --> 00:04:39.170 So we know what this area is, the area 00:04:39.170 --> 00:04:40.780 within two standard deviations. 00:04:40.780 --> 00:04:42.020 The empirical rule tells us. 00:04:42.020 --> 00:04:46.820 Or even better, the 68, 95, 99.7 rule 00:04:46.820 --> 00:04:48.830 tells us that this area-- because it's 00:04:48.830 --> 00:04:55.300 within two standard deviations-- is 95%, or 0.95. 00:04:55.300 --> 00:04:59.740 Or it's 95% of the area under the normal distribution. 00:04:59.740 --> 00:05:02.400 Which tells us that what's left over-- this tail 00:05:02.400 --> 00:05:04.880 that we care about and this left tail right here-- 00:05:04.880 --> 00:05:08.340 has to make up the rest of it, or 5%. 00:05:08.340 --> 00:05:12.216 So those two combined have to be 5%. 00:05:12.216 --> 00:05:13.570 And these are symmetrical. 00:05:13.570 --> 00:05:14.590 We've done this before. 00:05:14.590 --> 00:05:16.330 This is actually a little redundant from other problems 00:05:16.330 --> 00:05:17.250 we've done. 00:05:17.250 --> 00:05:20.010 But if these are added, combined 5%, and they're the same, 00:05:20.010 --> 00:05:22.580 then each of these are 2.5%. 00:05:22.580 --> 00:05:24.792 Each of these are 2.5%. 00:05:24.792 --> 00:05:26.250 So the answer to the question, what 00:05:26.250 --> 00:05:29.160 is the probability that a randomly chosen fifth grade boy 00:05:29.160 --> 00:05:32.820 would be taller then 157.7 centimeters. 00:05:32.820 --> 00:05:34.320 Well, that's literally just the area 00:05:34.320 --> 00:05:35.927 under this right green part. 00:05:35.927 --> 00:05:37.510 Maybe I'll do it in a different color. 00:05:37.510 --> 00:05:39.660 This magenta part that I'm coloring right now. 00:05:39.660 --> 00:05:40.920 That's just that area. 00:05:40.920 --> 00:05:43.600 We just figured out it's 2.5%. 00:05:43.600 --> 00:05:47.780 So there's a 2.5% chance we'd randomly find a fifth grade 00:05:47.780 --> 00:05:51.260 boy who's taller than 157.7 centimeters, 00:05:51.260 --> 00:05:53.650 assuming this is the mean, the standard deviation, 00:05:53.650 --> 00:05:56.680 and we are dealing with a normal distribution.