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Importance and Application of probability:
Importance of probability theory is in all those areas where event are not certain to take place as same as starting with games of chances. Probability has become one of the basis tools of statistics. Statistics and probability are much interrelated with each other that it is difficult to discuss statistics without understanding the meaning of probability. A knowledge of probability theory makes it easier, simpler and possible to interpret the statistical result, as many of the statistical procedures include involve conclusions based on samples which are randomly choosen.
Probability theory is being applied not only in mathematical problems but also for the solutions of social economical, political and business problems. The insurance insustry emerged in the 19th century, required exact or definite knowledge about the risk of loss inorder to calculate premium. Within few decades the concept of probability has assumed great importance and the mathematical theory of probability has become the basis of statistical application and social and decision making. In fact probability has become a part of everyone life. In personal and management decisions one faces uncertainty and uses probability theory. By organising information and considering it systematically, one will be able to recognise his or her assumptions, communicate his or reasoning to others and make a better decision than he or she could by using a shot in the dark approach. Probability theory in fact is the foundation of statistical conclusion or inference.
A marketing research firm was engaged by an automobile manufacturer to conduct a pilot study to examine the feasibility of using logistic regression for ascertaining the likelihood
a) What is meant by secular trend? Discuss any two methods of isolating trend values in a time series.
The data in the data frame compensation are from Myers (1990), Classical andModern Regression with Applications (Second Edition)," Duxbury. The response y here is executive compens
introduction of median
In the context of multivariate data analysis, one might be faced with a large number of v&iables that are correlated with each other, eventually acting as proxy of each other. This
Scenario: To fundraise for middle school camp the year 3 and 4 syndicate designed and produced chocolate treats to sell to the year 1 and 2, and year 5 and 6 students at morning te
Risk of Portfolios So far, we have seen the application of standard deviation in the context of risk in single investment. But usually most investors hold portfolios of securi
Calculation for Discrete Series or Ungrouped Data The formula for computing mean is = where, f = fr
Related Positional Measures Besides median, there are other measures which divide a series into equal parts. Important amongst these are quartiles, deciles and percentiles.
applications of normal probability distribution
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