Data Science different topic explanation -- Part-2 -- Events. Probabilities of events

If you missed the previous post, here’s the below mentioned link.

Data Science different topic explanation – Part-2 – Events. Probabilities of events

One of the basic concepts in statistics in an event. Events are simply results of experiments. Events can be certain impossible, or random.

A certain event is an event that as a result of an experiment (the execution of certain actions with a certain set of conditions) will occur in 100% cases. For instance, tossed coin will certainly fall (on the Earth conditions).

Impossible event - an event, as the name implies, that will not occur as a result of the experiment. For instance, tossed coin will fly in the sky – this is an “impossible event”.

Continued, above post for detailed content.

And finally, an event is called a random event if the event may or may not occur as a result of the experiment. There should be present fundamental criteria of randomness in such an experiment. A random event is a consequence of random factors which influence cannot be predicted or predictions can be extremely difficult. For the coin toss example, random factors are the shape and physical characteristics of the coin, the strength/direction the throw, air resistance, etc. These are factors that are extremely hard to predict.

Let us consider in more detail the flip of a coin (meaning a fair coin – a coin in which both results (“heads and tails”) are equally likely). There are 2 mutually exclusive outcomes – heads or tails. The outcome of the flip is random since the observer cannot analyse and take into account all the factors that influence the result.

What is the probability of heads? Most answer 1/2, but why? To get the answer follow the conversation series.

Continuing, above question’s answer.

Let’s name A the event that came up as tails. Let the coin be trown n times. Then the probability of event A can be defines as:

The probability of an event happening = number of ways it can happen / Total number of outcomes

This called the frequency of event A in a long series of tests.

Another example: There are 4 kings in a deck of 52 cards. What is the probability of picking a King?

Number of ways it can happen: 4 (there are 4 kings)

Total number of outcomes: 52 (there are 52 cards in total)

So the probability = 4/52 = 1/13.

It turns out that in various test series the corresponding frequency for large n. is fluctuating around a constant value P(A). This value is called the probability of event A and is denoted by the letter P - an abbreviation for Probability.

The probability lies in the range [0,1], where, in general, 0 indicates the impossibility of the event, and 1 indicates certainty. The higher the probability of an event, the greater the likelihood that an event will occur.

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Next post will be on Event Types.