Multiply the possible outcomes of the events in the disjoint events

They are the product of the number of possible outcomes for each of the component events.

Counting Principle is used to find the number of possible outcomes. It states that if an event has m possible outcomes and another independent event has n possible outcomes, then there are mn possible outcomes for the two events together.

I assume you mean how many possible outcomes when looking at all 13 results. It would be 2^13 = 8192

It is a set of events that, taken together, include all possible outcomes.

Because there are many events whose outcomes cannot be determined. However, using probability it may be possible to make a good estimate as to the outcome.Because there are many events whose outcomes cannot be determined. However, using probability it may be possible to make a good estimate as to the outcome.Because there are many events whose outcomes cannot be determined. However, using probability it may be possible to make a good estimate as to the outcome.Because there are many events whose outcomes cannot be determined. However, using probability it may be possible to make a good estimate as to the outcome.

Given any event, the complementary event consists of all other possible outcomes.Given any event, the complementary event consists of all other possible outcomes.Given any event, the complementary event consists of all other possible outcomes.Given any event, the complementary event consists of all other possible outcomes.

A set of events is said to be exhaustive if, between them, they cover all possible outcomes.

Random events are events that do not have a determined outcome. The set of possible outcomes for a random event is always greater than one item.

what major events occurred in 1958

Well you start with the first event, how many possibilities, draw a line down for each one, and state what event occurred. I.e. a heads or tails of a coin. Then from each of these outcomes, draw the possible outcomes from each of the first events reflecting the second events, i.e. HH, HT, TH, TT. Third outcome (third flip of a coin) would look like this. HHH, HHT, HTH, HTT, THH, THT, TTH, TTT

events that have one or more outcomes in common.

They are overlapping events.They are overlapping events.They are overlapping events.They are overlapping events.

true A compound event consists of two more outcomes or simple events

The order the events occurred in.

These events are said to be complementary.

The frequency distribution table lists all the possible events and how many times (frequency) they occurred.

Historical events which have occurred have a probability of 1. They are a certainty. This refers to the event itself, not some historian's or politician's interpretation of what happened. However, the probability that they will occur again depends on the event. Exact recurrence is impossible (probability = 0).

Two events are independent if the outcome of one has no effect on the probability of the outcomes for the other.

Chronological order arranges events in the order in which they occurred.

There are many events that occurred throughout the book Jane Eyre. Any of these events could be deemed last in any list.

Whether the events are independent or dependent, whether or not they are mutually exclusive.

a way to model random events, such that simulated outcomes closely match real-world outcomes. By observing simulated outcomes, researchers gain insight on the real world.

We say that these are independent events, meaning that the outcome of rolling the cube does not influence what outcome of rotating the spinner. For each outcome of rolling the cube there are 10 outcomes from the spinner. We can therefore, multiply the numbers of possibilities: 6 * 10 = 60 One way of seeing this is to list the possible outcomes : C1 S1 C1 S2 C1 S3 . . . C1 S10 Notice that there are 10 spinner possibilities for one cube event. There are 5 more possible cube events, hence, 50 combination events.

Your question is not clear, but I will attempt to interpret it as best I can. When you first learn about probability, you are taught to list out the possible outcomes. If all outcomes are equally probable, then the probability is easy to calculate. Probability distributions are functions which provide probabilities of events or outcomes. A probability distribution may be discrete or continuous. The range of both must cover all possible outcomes. In the discrete distribution, the sum of probabilities must add to 1 and in the continuous distribtion, the area under the curve must sum to 1. In both the discrete and continuous distributions, a range (or domain) can be described without a listing of all possible outcomes. For example, the domain of the normal distribution (a continuous distribution is minus infinity to positive infinity. The domain for the Poisson distribution (a discrete distribution) is 0 to infinity. You will learn in math that certain series can have infinite number of terms, yet have finite results. Thus, a probability distribution can have an infinite number of events and sum to 1. For a continuous distribution, the probability of an event are stated as a range, for example, the probability of a phone call is between 4 to 10 minutes is 10% or probability of a phone call greater than 10 minutes is 60%, rather than as a single event.

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