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# Statistics home work

In y ways, ad each of these ways (k+y) are likely to happen in equal measure, ten the probability (the chance) of its happening is k/(k+y) and of its failure is y/(k+y). P(A/B) = P (A and B)/P (B), were the vertical bas, / represent conditioning (given). This illustration therefore, mans that a major difference that exist between the normal probability and conditional probability of an event occurring is that an event in a conditional probability case occurs if and only if another event has occurred whereas in a probability situation, te chance of an event occurring is based on the ratio of the number of favorable events to the total number of equally likely events.

Bsed on the analysis of the conditional probability described above, te Bayes’ theorem shows how to invert the conditional probabilities. The theory, mdeled by Bayes (1702-1761) is concerned with estimation of probabilities of the cases by which an observed event may have been produced. Te theory states that if events A1, 2…. A become mutually exclusive events whose union is universe, another arbitrary event, B happens to be in the universe such that P(A)≠0, ad given thatThe main purposes of variance and standard deviation and how the probability principle would interact with the variance and standard deviation concepts: a empirical example from the business environment of usefulness of this concept in business decision making informationThe deviations scores from the mean of a distribution have become the main statistical tests of variations when making decision.

Mking decisions on the dispersions of the various sets of scores about the mean is very when determining the variability of the options available for making a choice.

Dviations about the mean are expressed in terms of the variance or standard deviation. I this case therefore, i is important for the management of firms to be able to grasp the concept of deviation and standard deviation since they are influential in determining variability of decision variables. Te statistical inferences such as variance and standard deviations are directly linked to the principle of probability in the sense that the processes of modeling a probability concept use and standard deviations.

A argued above, i is clearly true that deviations scores from the mean of a distribution have become the main statistical tests of variations when making decision and are thus important in determining...

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