watch a TED Talk that discusses real-world contexts in which statistical decision making is crucial and consequential
Statistic in Everyday life
Decisions we make in everyday life are all based on probability but often in an intuitive way. For example if a family member gets a positive screening for cancer or another disease this is a probabilistic determination based on the measurement made. Similarly when police arrest individuals or juries convict them they do so based on probabilistic determinations (e.g. how likely is it that this evidence would exist if the person were innocent?). Even mundane decisions like when to leave for work to arrive on time are based on probabilistic determinations. You cannot know that leaving at a certain time will mean arriving on time because there are a variety of variables you may fail to consider. However you can make reasonable inferences based on probability given the variables about which you are aware (e.g. traffic patterns risk of accidents existing construction etc.). Clearly statistical decision making inundates our lives whether we are aware of it or not.
First you will watch a TED Talk that discusses real-world contexts in which statistical decision making is crucial and consequential: How Juries Are Fooled by Statistics. (Note: Pay special attention to the video from 10:47 to end.) As you answer the discussion questions think about the statistical concepts you learned in this module regarding statistical decision making such as true and false positives and negatives. You will write about the ways that statistical decision making is involved in many areas of our daily life and demonstrate your understanding of these key concepts related to inferential statistical decision making.
For your initial post review the video and address the following:
How do the examples given in the video (jury decisions and medical tests) connect to what you learned about statistical decision making related to Type I errors (false positives) and Type II errors (false negatives)? Select either Type I errors or Type II errors and explain your response.
In general do you think that making Type I or Type II errors is worse?
Do you think the context in which the statistical decision is being made affects which of the errors is worse?
For example if you think about scientific research into curing cancer or jury decisions about criminal convictions or scheduling decisions to get to work on time do you feel that the negative effects of Type I and Type II errors are similar or different across these contexts?
Given your earlier discussion about the importance of statistical thinking for effective citizenship and what you have learned in the course in general and this module specifically do you still hold the same view about the importance of statistical thinking for the general population? Why or why not?