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THE ROLE OF STATISTICS IN DECISION MAKING
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95 percent confidence accept H0 advertising alpha level analysis of variance apply beta binomial distribution calculated cars chance chi-square coefficient conditional probability confidence interval confidence interval estimate confidence level correlation cost critical value customers decide decision makers need Decision Rule defective degrees of freedom determine develop difference Discuss elementary events employees equal equation example expected value Figure forecasting frequency distribution hypothesis test independent variable indicate interval estimate linear manager manufacturer measure median method N-XI normal distribution null hypothesis oooo ounces outcomes payoff percent confidence interval point estimate Poisson distribution population mean posterior probabilities probability distribution production random variable Referring to problem regression analysis regression line regression model reject H0 relative frequency sample information sample mean sampling distribution selected simple random sample standard deviation standard error statistical Suppose Table techniques trucks true Type II error variation zero