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coefficient of determination the coefficient of determination is given by r2 ie the square of the correlation coefficient it explains to what extent
caveatwe must be careful when interpreting the meaning of association although two variables may be associated this association does not imply that
significance of correlationthe study of correlation is of immense use in practical life correlation analysis contributes to the understanding of
correlationthe board of directors of bata company is faced with the problem of estimating what the annual sales might be in a shop to be opened in
type i and ii errorsif a statistical hypothesis is tested we may get the following four possible casesthe null hypothesis is true and it is
sampling error it is the difference between the value of the actual population parameter and the sample statisticsamples are used to arrive at
statistics can lead to errors the use of statistics can often lead to wrong conclusions or wrong estimates for example we may want to find out the
cluster sampling here the population is divided into clusters or groups and then random sampling is done for each cluster cluster sampling differs
stratified sampling stratified sampling is generally used when the population is heterogeneous in this case the population is first subdivided into
systematic sampling in systematic sampling each element has an equal chance of being selected but each sample does not have the same chance of
simple random samplingin simple random sampling each possible sample has an equal chance of being selected further each item in the entire population
advantages of samplingwhy should we settle on a sample instead of studying the entire population sampling has the following advantages over a
introduction to probabilitya student is considering whether she should enroll in an mba educational program offered by a
risk of portfoliosso far we have seen the application of standard deviation in the context of risk in single investment but usually most investors
coefficient of variationthe standard deviation discussed above is an absolute measure of dispersion the corresponding relative measure is known as
variancethe term variance was used to describe the square of the standard deviation by rafisher the concept of variance is highly important in
root mean square deviationthe standard deviation is also called the root mean square deviation this is because it is theroot step 4of the mean step
rangeofficial exports target 2000-2001product millionplantation500agriculture and allied products2255marine products650ores amp minerals869leather
measures of dispersion box 3 food vs oilbelow are the figures for foodgrain procurement and crude oil
comparison of the principal averages-mean median and modethe mean median and mode are located at the same point in a
there are situations where none of the three averages is fully satisfactory for example if the number of items in a series is very
empirical modewhere mode is ill-defined its value may be ascertained by the following formula based upon the empirical relationship between mean
disadvantagesthe value of mode cannot always be determined in some cases we may have a bimodal seriesit is not capable of algebraic manipulations
advantagesby definition mode is the most typical or representative value of a distribution hence when we talk of modal wage modal size of shoe or
there may be two values which occur with the same maximum frequency the distribution is then called bimodal in a bimodal distribution the value