AP statisticsModel Syllabus using StarnesWord下载.docx

1、W. H. Freeman & Co., 2014.Review text: Barrons AP Statistics （7th edition）, by Sternstein, Barrons Ed. Series, 2013.Flash cards: Barrons AP Statistics Flash Cards, （2nd edition）, by Sternstein,Barrons Educational Series, 2014.COURSE OUTLINE:Chapter 1DayTopicsLearning Objectives Students will be able

2、 to Suggested assignment1Chapter 1 Introduction Identify the individuals and variables in a set of data. Classify variables as categorical or quantitative.1, 3, 5, 7, 821.1 Bar Graphs and Pie Charts, Graphs: Good and Bad Display categorical data with a bar graph. Decide if it would be appropriate to

3、 make a pie chart. Identify what makes some graphs of categorical data deceptive.11, 13, 15, 1731.1 Two-Way Tables and Marginal Distributions, Relationships between Categorical Variables: Conditional Distributions Calculate and display the marginal distribution of a categorical variable from a two-w

4、ay table. Calculate and display the conditional distribution of a categorical variable for a particular value of the other categorical variable in a two-way table. Describe the association between two categorical variables by comparing appropriate conditional distributions. 19, 21, 23, 25, 273241.2

5、Dotplots, Describing Shape, Comparing Distributions, Stemplots Make and interpret dotplots and stemplots of quantitative data. Describe the overall pattern （shape, center, and spread） of a distribution and identify any major departures from the pattern （outliers）. Identify the shape of a distributio

6、n from a graph as roughly symmetric or skewed. Compare distributions of quantitative data using dotplots or stemplots.37, 39, 41, 43, 45, 4751.2 Histograms, Using Histograms Wisely Make and interpret histograms of quantitative data. Compare distributions of quantitative data using histograms.53, 55,

7、 59, 60, 65, 697461.3 Measuring Center: Mean and Median, Comparing the Mean and Median, Measuring Spread: Range and IQR, Identifying Outliers, Five-Number Summary and Boxplots Calculate measures of center （mean, median）. Calculate and interpret measures of spread （range, IQR）. Choose the most approp

8、riate measure of center and spread in a given setting. Identify outliers using the 1.5IQR rule. Make and interpret boxplots of quantitative data.79, 81, 83, 87, 89, 91, 9371.3 Measuring Spread: Standard Deviation, Choosing Measures of Center and Spread, Organizing a Statistics Problem Calculate and

9、interpret measures of spread （standard deviation）. Use appropriate graphs and numerical summaries to compare distributions of quantitative variables. 95, 97, 99, 103, 105, 1071108Chapter 1 Review/FRAPPY!Chapter 1 Review Exercises9Chapter 1 TestChapter 2Learning Objectives Students will be able to 2.

10、1 Measuring Position: Percentiles; Cumulative Relative Frequency Graphs; Measuring Position: z-scores Find and interpret the percentile of an individual value within a distribution of data. Estimate percentiles and individual values using a cumulative relative frequency graph. Find and interpret the

11、 standardized score （z-score） of an individual value within a distribution of data.1, 3, 5, 9, 11, 13, 152.1 Transforming Data Describe the effect of adding, subtracting, multiplying by, or dividing by a constant on the shape, center, and spread of a distribution of data.17, 19, 21, 23, 25302.2 Dens

12、ity Curves, The 689599.7 Rule; The Standard Normal Distribution Estimate the relative locations of the median and mean on a density curve. Use the 689599.7 rule to estimate areas （proportions of values） in a Normal distribution. Use Table A or technology to find （i） the proportion of z-values in a s

13、pecified interval, or （ii） a z-score from a percentile in the standard Normal distribution.33, 35, 39, 41, 43, 45, 47, 49, 512.2 Normal Distribution Calculations Use Table A or technology to find （i） the proportion of values in a specified interval, or （ii） the value that corresponds to a given perc

14、entile in any Normal distribution.53, 55, 57, 592.2 Assessing Normality Determine if a distribution of data is approximately Normal from graphical and numerical evidence.54, 63, 65, 66, 67, 6974Chapter 2 Review/FRAPPY!Chapter 2 Review ExercisesChapter 2 TestChapter 3Chapter 3 Introduction3.1 Explana

15、tory and response variables, displaying relationships: scatterplots, describing scatterplots Identify explanatory and response variables in situations where one variable helps to explain or influences the other. Make a scatterplot to display the relationship between two quantitative variables. Descr

16、ibe the direction, form, and strength of a relationship displayed in a scatterplot and recognize outliers in a scatterplot.1, 5, 7, 11, 133.1 Measuring linear association: correlation, facts about correlation Interpret the correlation. Understand the basic properties of correlation, including how th

17、e correlation is influenced by outliers. Use technology to calculate correlation. Explain why association does not imply causation.1418, 213.2 Least-squares regression, interpreting a regression line, prediction, residuals Interpret the slope and y intercept of a least-squares regression line. Use t

18、he least-squares regression line to predict y for a given x. Explain the dangers of extrapolation. Calculate and interpret residuals.2732, 35, 37, 39, 41, 453.2 Calculating the equation of the least-squares regression line, determining whether a linear model is appropriate: residual plots Explain th

19、e concept of least squares. Determine the equation of a least-squares regression line using technology. Construct and interpret residual plots to assess if a linear model is appropriate.43, 47, 49, 513.2 How well the line fits the data: the role of s and r2 in regression Interpret the standard devia

20、tion of the residuals and and use these values to assess how well the least-squares regression line models the relationship between two variables.48, 50, 55, 583.2 Interpreting computer regression output, regression to the mean, correlation and regression wisdom Determine the equation of a least-squ

21、ares regression line using computer output. Describe how the slope, y intercept, standard deviation of the residuals, and are influenced by outliers. Find the slope and y intercept of the least-squares regression line from the means and standard deviations of x and y and their correlation.59, 61, 63

22、, 65, 69, 7178Chapter 3 Review/FRAPPY!Chapter Review ExercisesChapter 3 TestChapter 4Learning Objectives Students will be able to4.1 Introduction, The Idea of a Sample Survey, How to Sample Badly, How to Sample Well: Simple Random Sampling Identify the population and sample in a statistical study. I

23、dentify voluntary response samples and convenience samples. Explain how these sampling methods can lead to bias. Describe how to obtain a random sample using slips of paper, technology, or a table of random digits.1, 3, 5, 7, 9, 114.1 Other Random Sampling Methods Distinguish a simple random sample

24、from a stratified random sample or cluster sample. Give the advantages and disadvantages of each sampling method.13, 17, 19, 21, 23, 254.1 Inference for Sampling, Sample Surveys: What Can Go Wrong? Explain how undercoverage, nonresponse, question wording, and other aspects of a sample survey can lea

25、d to bias.27, 29, 31, 33, 354.2 Observational Study versus Experiment, The Language of Experiments Distinguish between an observational study and an experiment. Explain the concept of confounding and how it limits the ability to make cause-and-effect conclusions.3742, 45, 47, 49, 51, 53, 554.2 How to Exper