Chapter 1: Exploring Data
In this chapter, students will learn how to classify variables as either categorical or quantitative. They will also be able to make and interpret dotplots and stemplots (with or without split stems) of quantitative data. Additional skills will include comparing distributions of quantitative data using dotplots, stemplots, or histograms.
Chapter 2: Modeling Distributions of Data
In this chapter, students will learn how to find and interpret the percentile of an individual value within a distribution of data. They will also be able to find and interpret the standardized score (z-score) of an individual value within a distribution of data. Additional skills include using the 68-95-99.7 rule to estimate areas (proportions of values) in a Normal distribution and using Table A or technology to find the proportion of z-values in a specified interval.
Chapter 3: Describing Relationships
This chapter will cover how to identify explanatory and response variables in situations where one variable helps to explain or influences the other. Students will also be able to define and interpret correlation, interpret the slope and y-intercept of a least-squares regression line, and use the least-squares regression line to predict y for a given x. Additional skills include calculating and interpreting residuals and describing how the slope, y-intercept, standard deviation of the residuals, and are influenced by outliers.
Chapter 4: Designing Studies
In this chapter, students will learn how to obtain a random sample using slips of paper, technology, or a table of random digits. They will also be able to distinguish a simple random sample from a stratified random sample or cluster sample and give the advantages and disadvantages of each sampling method. Additional skills include distinguishing between an observational study and an experiment.
Chapter 5: Probability: What are the Chances?
This chapter covers interpreting probability as a long-run relative frequency, using basic probability rules (including the complement rule and the addition rule for mutually exclusive events), using a two-way table or Venn diagram to model a chance process and calculate probabilities involving two events, using the general addition rule to calculate probabilities, and calculating and interpreting conditional probabilities.
Chapter 6: Random Variables
In this chapter, students will be able to compute probabilities using the probability distribution of a discrete random variable, calculate and interpret the mean (expected value) of a discrete random variable, calculate and interpret the standard deviation of a discrete random variable, compute probabilities using the probability distribution of certain continuous random variables, find the mean and standard deviation of the sum or difference of independent random variables, determine whether the conditions for using a binomial random variable are met, compute and interpret probabilities involving binomial distributions, and find probabilities involving geometric random variables.
