l Chapter 1-Key terms Collection, summarization, analysis, and reporting of numerical findings Statistics-Two Usages A. The study of statistics B. Statistics as reported sample measures

J Chapter 7- Learning objectives Differentiate between the normal and the exponential distributions Use the standard normal distribution and z-scores to determine probabilities associated with the normal distribution Use the normal distribution to approximate the binomial distribution Use the exponential distribution to determine related

Sampling distribution of the mean When the population is normally distributed Shape: Regardless of sample size, the distribution of sample means will be normally distributed Center: The mean of the distribution of sample means is the mean of the population. Sample size does not affect the center of the distribution

Chapter 10-Learning Objectives Describe the logic of and transform verbal statements into null and alternative hypotheses Describe what is meant by Type I and Type Il errors Conduct a hypothesis test for a single population mean or proportion

Chapter 13-Learning objectives Explain the nature of the chi-square distribution Apply the chi-square distribution to Goodness-of-fit tests Tests of independence between 2 variables Tests comparing proportions from multiple populations Tests of a single population variance o 2002 The Wadsworth Group

Chapter 14-Learning objectives Differentiate between nonparametric and parametric hypothesis tests Determine when a nonparametric test should be used instead of its parametric counterpart Appropriately apply each of the nonparametric methods introduced o 2002 The Wadsworth Group

Chapter 17-Learning Objectives Build polynomial regression models to describe curvilinear relationships Apply qualitative variables representing two or three categories Use logarithmic transforms in constructing exponential and multiplicative models Identify and compensate for multicollinearity Apply stepwise regression

Chapter 19- Learning Objectives Express a decision situation in terms of decision alternatives, states of nature, and payoffs. Differentiate between non-Bavesian and Bavesian decision criteria. Determine the expected payoff for a decision alternative. Calculate and interpret the expected value of perfect information

Chapter 20-Learning Objectives Understand the philosophy of total quality management(TQM) Be able to distinguish between defect prevention and defect detection strategies for the management of qualit Be able to distinguish random variation from assignable variation Understand the fundamentals of statistical process control charts

Chapter 18-Learning Objectives Describe the trend, cyclical, seasonal, and irregular components of the time series model Fit a linear or quadratic trend equation to a time series Smooth a time series with the centered moving average and exponential smoothing techniques