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Part 1: Using your own words, describe two events that are independent. Use math vocabulary that you have learned so far in this module to explain what it means when events are independent. Part 2: Define an issue that is important to you (politics, medicine, social media, education, etc.), and think about some things you might want to know about this issue. Briefly explain your issue and what you hope to learn or understand. Pose a question for which a two-way table is appropriate. Be creative here! Collect data from at least 20 people (or other sources). Display your data in a two-way frequency table like the one shown below. Your table can have more rows or columns if you need them. Choose a row and column and compare P(A | B) with P(B | A). Explain what each probability means in the context of the situation and data you collected. Compare P(A∩B) with P(A∪B), and explain what each probability means in the context of the situation and data you collected. Answer the following reflective questions about completing question 3: Why did you choose this topic? How did you collect your data? What challenges did you encounter in the data collection, data display, or data analysis? How did you overcome these challenges?
Two events, A and B, are independent if the fact that A occurs does not affect the probability of B occurring. Some other examples of independent events are: Landing on heads after tossing a coin AND rolling a 5 on a single 6-sided die. Choosing a marble from a jar AND landing on heads after tossing a coin. Choosing a 3 from a deck of cards, replacing it, AND then choosing an ace as the second card. Rolling a 4 on a single 6-sided die, AND then rolling a 1 on a second roll of the die. To find the probability of two independent events that occur in sequence, find the probability of each event occurring separately, and then multiply the probabilities. This multiplication rule is defined symbolically below. Note that multiplication is represented by AND. Multiplication Rule 1: When two events, A and B, are independent, the probability of both occurring is: P(A and B) = P(A) · P(B)
This is extremely confusing xD
lol hold on
When two events are said to be independent of each other, what this means is that the probability that one event occurs in no way affects the probability of the other event occurring. An example of two independent events is as follows; say you rolled a die and flipped a coin. The probability of getting any number face on the die in no way influences the probability of getting a head or a tail on the coin.
Okay, that makes more since. In the part two how would you relate that to like politics?? thats where im getting confused the most
Politics is a mind-killer: tribal feelings readily degrade the analytical skill and impartiality of otherwise very sophisticated thinkers, and so discussion of politics (even in a descriptive empirical way, or in meta-level fashion) signals an increased probability of poor analysis. I am not a political partisan and am raising the subject primarily for its illustrative value in thinking about small probabilities of large payoffs.
uhmm, can we maybe pick something else because politics are already confusing and that just threw me off lol
probability distribution is a statistical model that shows the possible outcomes of a particular event or course of action as well as the statistical likelihood of each event. For example, a company might have a probability distribution for the change in sales given a particular marketing campaign. The values on the "tails" or the left and right end of the distribution are much less likely to occur than those in the middle of the curve.
Academic research has consistently found that people who consume more news media have a greater probability of being civically and politically engaged across a variety of measures. In an era when the public’s time and attention is increasingly directed toward platforms such as Facebook and Twitter, scholars are seeking to evaluate the still-emerging relationship between social media use and public engagement.