Examples of event in the following topics:
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- The complement of $A$ is the event in which $A$ does not occur.
- In probability theory, the complement of any event $A$ is the event $[\text{not}\ A]$, i.e. the event in which $A$ does not occur.
- Generally, there is only one event $B$ such that $A$ and $B$ are both mutually exclusive and exhaustive; that event is the complement of $A$ .
- The complement of an event $A$ is usually denoted as $A'$, $A^c$ or $\bar{A}$.
- Finally, let's examine a non-example of complementary events.
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- Events organized around a new product/service launch are typically postponed or cancelled because the new product/service does not turn out as anticipated.Build this scenario into any planned event so that you can recoup some of the costs if the event needs to be cancelled.
- Is the new product going to be fully functional in time for the event?
- Have you determined your budget for the new product launch event?
- Have you devised the best forum for the new product launch event?
- Is the event scheduled during an industry tradeshow where everyone will already be assembled and you can easily fold your event into the bigger show, leveraging all the resources available at that event?
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- Two events A and B are independent if the knowledge that one occurred does not affect the chance the other occurs.
- For example, the outcomes of two roles of a fair die are independent events.
- To show two events are independent, you must show only one of the above conditions.
- If two events are NOT independent, then we say that they are dependent.
- The events are considered to be dependent or not independent.
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- Examples of PR are publicity, press releases, press conferences, interviews, and events.
- Examples of PR events are product events, corporate events, and community events.
- Press kits or information packs are usually handed out at these events.
- Events – Organisations usually have limited control here. 3 major types of events exist namely: · Product Events - are aimed at increasing sales e.g. celebrity book signing, opening of new stores etc aimed at creating awareness and interest in products being provided. · Corporate Events – These events are aimed at developing corporate bodies and usually generate a lot of local media coverage.
- These events facilitate awareness, goodwill and interest e.g. open days and factory/warehouse visits. · Community Events – These help and contribute to local communities.
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- An impossible event, or an event that never occurs, has a probability of $0$.
- An event that always occurs has a probability of $1$.
- The probability that an event does not occur is $1$ minus the probability that the event does occur.
- These events are called complementary events, and this rule is sometimes called the complement rule.
- Suppose $A$ is the event exactly one head occurs, and $B$ is the event exactly two tails occur.
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- The conditional probability of an event is the probability that an event will occur given that another event has occurred.
- Our estimation of the likelihood of an event can change if we know that some other event has occurred.
- The conditional probability $\displaystyle P(B|A)$ of an event $B$, given an event $A$, is defined by:
- Suppose that $B$ is the event that at least one heads occurs and $A$ is the event that all $3$ coins are the same.
- If the knowledge that event $A$ occurs does not change the probability that event $B$ occurs, then $A$ and $B$ are independent events, and thus, $P(B|A) = P(B)$.
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- Both actors and events are treated as nodes, and lines are used to show the connections of actors to events (there will be no lines from actors to actors directly, or from events to events).
- Actors that are close together (e.g. the Cahualla and Morongo Indians in the lower left corner) are connected because they have similar profiles of events.
- And, particular donors are located in the same parts of the space as certain initiatives -- defining which issues (events) tend to go along with which actors.
- It is exactly this kind of "going together-ness" or "correspondence" of the locations of actors and events that the numeric methods discussed below are intended to index.
- That is, the numeric methods are efforts to capture the clustering of actors brought together by events; events brought together by the co-presence of actors; and the resulting "bundles" of actors/events.
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- Factor analysis provides an alternative method to SVD to the same goals: identifying underlying dimensions of the joint space of actor-by-event variance, and locating or scaling actors and events in that space.
- This solution, although different from SVD, also suggests considerable dimensional complexity in the joint variance of actors and events.
- "left/right") do not provide very accurate predictions about the locations of individual actors or events.
- Figure 17.12 shows the loadings of the events.
- To visualize the patterns, the loadings of actors and events on the dimensions could be extracted from output data files, and graphed using a scatterplot.