A First Course in Statistics
This book presents balanced coverage of the theory and application of statistics while enhancing reader's critical thinking skills.This book shows readers that knowledge of statistics is important to their own lives. Almost all of the I examples and exercises are based on current, real-world applications pulled from journals, magazines, news articles, and commerce. Presents the importance of data collection, observations, experiments, and surveys in drawing meaningful inferences from data. Now provides an equal balance between applications relying on p-values and those relying on critical values in their interpretation.
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alternative hypothesis approximately normal Assume assumptions average binomial probability binomial random variable box plot brand calculate Central Limit Theorem Chapter confidence interval corresponding data provide sufficient data set Describe determine discrete random variable drug equal example experiment Find the probability frequency histogram graph independent inference Interpret large-sample Learning the Mechanics least squares line manufacturer mean and standard median mileage Minitab mound-shaped normal distribution null and alternative null hypothesis observed significance level p-value percentage population mean prediction probability distribution proportion provide sufficient evidence purchase random sample randomly selected Refer to Exercise reject H0 rejection region relative frequency histogram sample mean sample space sample statistic sampling distribution scores shown in Figure simple events Solution standard deviation standard normal stem-and-leaf display Suppose Table test of hypothesis test statistic toss two-tailed Type II error variance Venn diagram z-score