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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:03,090 --> 00:00:04,050 Instructor: Hello everyone, 2 00:00:04,050 --> 00:00:05,670 in this video, we are going to introduce 3 00:00:05,670 --> 00:00:09,573 a very useful concept in probability, the additive law. 4 00:00:11,130 --> 00:00:12,870 Recall when we introduced the concept 5 00:00:12,870 --> 00:00:14,793 of unions earlier in the course. 6 00:00:15,630 --> 00:00:18,570 We said that the union of two events, A and B, 7 00:00:18,570 --> 00:00:21,693 is equal to their sum minus their intersection. 8 00:00:23,190 --> 00:00:26,070 The additive law states something very similar. 9 00:00:26,070 --> 00:00:28,530 The probability of the union of two sets 10 00:00:28,530 --> 00:00:31,920 is equal to the sum of the individual probabilities 11 00:00:31,920 --> 00:00:36,123 of each event minus the probability of their intersection. 12 00:00:37,320 --> 00:00:39,820 Let's go back to the survey from the last lecture. 13 00:00:40,800 --> 00:00:44,220 The union of women and vegetarians equal the sum 14 00:00:44,220 --> 00:00:48,270 of probabilities of being a woman and being a vegetarian 15 00:00:48,270 --> 00:00:51,243 minus the probability of being a vegetarian woman. 16 00:00:52,290 --> 00:00:57,290 Numerically, this equals 0.47 plus 0.44 minus 0.15, or 0.76. 17 00:01:02,250 --> 00:01:04,260 Thus, if we picked a random person 18 00:01:04,260 --> 00:01:07,260 from the survey there is a 76% chance 19 00:01:07,260 --> 00:01:10,593 they're either female, vegetarian, or both. 20 00:01:12,000 --> 00:01:14,310 Now, look at a different example. 21 00:01:14,310 --> 00:01:16,830 Suppose we know 38% of our colleagues 22 00:01:16,830 --> 00:01:21,817 can proficiently use Tableau and 45% are experts in SQL. 23 00:01:22,950 --> 00:01:25,470 Additionally, 66% of the people 24 00:01:25,470 --> 00:01:28,203 in the office are good with at least one of the two. 25 00:01:29,160 --> 00:01:31,110 What is the probability of somebody being able 26 00:01:31,110 --> 00:01:34,683 to simultaneously implement SQL and Tableau? 27 00:01:35,640 --> 00:01:37,560 To answer this, we can rearrange 28 00:01:37,560 --> 00:01:39,810 the additive law to get the intersection 29 00:01:39,810 --> 00:01:43,230 of Tableau and SQL users equals the sum 30 00:01:43,230 --> 00:01:47,520 of SQL and Tableau users minus their union. 31 00:01:47,520 --> 00:01:49,830 Plugging in the values we are given results 32 00:01:49,830 --> 00:01:54,830 in 38% plus 45% minus 66%, or 17%. 33 00:01:58,380 --> 00:02:00,930 Transforming this into a probability gives us 34 00:02:00,930 --> 00:02:04,560 a likelihood of 0.17 for somebody in the office 35 00:02:04,560 --> 00:02:08,613 to be able to proficiently implement SQL and Tableau. 36 00:02:10,139 --> 00:02:11,730 Certain events require the usage 37 00:02:11,730 --> 00:02:14,313 of a new concept called the multiplication rule. 38 00:02:15,420 --> 00:02:16,920 In the next lecture, we are going 39 00:02:16,920 --> 00:02:20,823 to discuss when and how we apply it, thanks for watching. 3215

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