Statistics asically deals with the collection and interpretation of the data based
on certain parameters which lead to significabnt results .Various important characteristics such as mean and variance of the data can be calculated and hence used for comparing two sets of data based on these parameters. Parameters such as coefficient of variation also determine the disprseion or variability of the population around a given mean. The three measures of central tendency that is Mean, Median and mode are basically used to draw a comparison between any sets of data. In Appling statistics to industrial and societal inferences we need to study a population and then draw conclusions. Sometimes studying the entire population becomes difficult hence we need to study a sample that is small in size
in order to lower the cost of collecting data in surveys. The data can then serve two purposes namely stastical and inferential.Despcritive data summarize the data by describing what is observed numerically or graphically. Inferential statistics uses pattern in sample data to provide inferences about the population represented accounting for randomness. These inferences may be used to answer yes/no questions like hypothesis testing describing association within the data in the form of correlation and regression. Randomness in the data observed is studied using the mathematics of probability distribution .Probability is used in statistical distribution of sample theory to study the sampling distribution of sample statistics and also the properties of statistical procedures.
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