Introduction to Mathematical Statistics
Probability; Nature of statistical methods; Empirical frequency distributions of one variable; Theoretical frequency distributions of one variable; Elementary sampling theory for one variable; Correlation and regression; Theoretical frequency distributions for correlation and regression; General principles for testing hypotheses and for estimation; Testing goodness of fit; Small sample distributions; Statistical design in experiments; Nonparametric methods.
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Sampling Theory IIS 5 Sampling Theory
Probability Distributions for Correlation and Regression
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accept applied approximation assume balls becomes binomial calculate called Chapter choose chosen conditional consequently consider continuous corresponding critical region curve defined definition degrees of freedom denote density function derivation desired determine discrete discussion equal equation error estimate event example expected experiment expressed fixed follows formula frequencies given gives graph hence hypothesis illustration independent inequality integral interval known least likelihood limits maximum mean measure methods moments necessary normal variable normally distributed observed obtained occur parameters percent points Poisson population possess possible preceding probability problem properties random sample random variable regression represent respect result sample mean sample points sample space satisfy selected shown simple solve squares standard statistical studying successes Suppose Table taken technique theorem treated trials true values variance yield