[lab-reading-stats-concepts] - Joan Concha

Lab_answers.md

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+## Challenges
+
+### Challenge 1: What is the difference between expected value and mean?
+
+The mean is total sum of observations, divided by the total number of observations, as simple as that.
+In other hand, the expected value is the average value we expect to get when we repeat an experiment a lot of times.
+
+### Challenge 2: What is the "problem" in science with p-values?
+
+There are two problems in my opinion: the first one is that the p-value is misinterpretated a lot of times, for example, let's see this 
+example: url = https://blog.minitab.com/blog/adventures-in-statistics-2/how-to-correctly-interpret-p-values
+
+For example, suppose that a vaccine study produced a P value of 0.04. This P value indicates that if the vaccine had no effect, you’d obtain the observed difference or more in 4% of studies due to random sampling error. The correct way to interpretate this is:
+
+Correct: Assuming that the vaccine had no effect, you’d obtain the observed difference or more in 4% of studies due to random sampling error.
+
+Incorrect: If you reject the null hypothesis, there’s a 4% chance that you’re making a mistake.
+
+The second problem is that, it is generally expected that a study should have a P < 0.05 as way to avoid considering 'statistically non-significant' outliers, that threshold can lead scientists to disregard data to keep within the P < 0.05, without considering whether the data is significant or not.
+
+### Challenge 3: Applying testing to a specific case: A/B testing.
+
+I chose the netflix article. On this article they try to demonstrate if changing the art of a picture they were able to increase the active time of the subscribers. I think that it would also be interesting to test different regions, and to point the main characteristics of the art with bigger results.