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If you're nervous about passing, consider taking a practice test first. Independent events will be discussed in more detail later in the lesson.Before you can take the behind-the-wheel test needed to obtain your driver's license, you'll need to take a written knowledge test. This is reflective of events that are not independent i.e.
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This means that given the student is a graduate, changes the likelihood that the student is a female. In this scenario, the marginal probability is not the same as the conditional probability. Note that this is not the same as the probability that a selected student is a female graduate student (ie. The total is just the number of graduate students (5000). We now are interested in only graduate students who are female (2213). If it is known that the student is a graduate student, what is the probability that the student is a female?
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The two-way table below displays the World Campus enrollment from Fall 2015 in terms of level (undergraduate and graduate) and biological sex.Ĭhoose one student from the sample, what is the probability that the student is a female?
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For instance, a team might have a probability of 0.6 of winning the Super Bowl or a country a probability of 0.3 of winning the World Cup. The time of day does not affect the quickest way.Īnother example is practically any sporting event. If you respond that it does not, this reflects the concept of "independence" as the quickest way is the same regardless of when your friend leaves.
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If you respond that it does, this reflects the concept of "conditional" as the quickest way is conditioned, or affected, by the time of day your friend leaves. The friend asks if leaving during rush hour would change these plans. For instance, say you are discussing driving directions with a friend on the quickest way to get to some destination. You can possibly imagine several daily conversations you may have that invoke these concepts. The concept of conditional events and independent events determines whether or not one of the events has an effect on the probability of the other event.
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