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Syllabus for AP Statistics Course Description Curriculum for this course follows the AP Statistics curriculum set by the College Board. While this syllabus is geared towards preparing students for the AP Statistics exam in May, a key ingredient to the course will be the paired student projects meant to teach students not only to gather, analyze, and make valid conclusions about data correctly, but to present their work effectively to a group while using the technology made available to them. Course material will focus on four major areas: exploratory data analysis, designing a study, probability, and statistical inference. Students will learn how to use TI-83 Plus or equivalent graphing calculators and Microsoft Excel in order to come to logical conclusions from data analysis and statistical and hypothesis testing. Additionally, students will be engaged in creating, compiling, and analyzing data stemming from in-class activities, observational studies, and experiments; active participation in these will allow students to gain a deeper understanding of the concepts and techniques of statistics. Primary Text Yates, Moore & Starnes. The Practice of Statistics. 3rd ed., W.H. Freeman & Co., 2008 Supplementary Texts Rossman, Chance & Barr von Oehson. Workshop Statistics. 3rd ed., Key College Publishing., 2008 Prep for the AP Exam Guide for Yates, Moore, and Starnes’s The Practice of Statistics, 3rd ed., Legacy. Technology All students will be issued or will own a TI-83 Plus or equivalent graphing calculator for use in class, at home, and on the AP Exam. Students will use their graphing calculator extensively throughout the course. Students will also extensively use Microsoft Excel for analyzing data and hypothesis testing; students will be required to use Microsoft PowerPoint in order to present the findings of their student projects. Course Projects In pairs, students will design and conduct a sample survey, an observational study, an experiment, and one of their own choosing from these three using the statistical techniques learned during each quarter of the course. These projects will involve the collection of data or the use of available data, the analysis of data using descriptive and inferential statistics, and the drawing of conclusions from their statistical analysis. Students are required to submit a written report and conduct an oral presentation utilizing Microsoft PowerPoint to visually display the findings of their research and display the results of their statistical testing using the TI-83 calculator or using Microsoft Excel. . Units of Study Content/Skills Resources Time Frame Unit 1: Exploration of Data YMS Chapter P, 10 class Students will be able to: Chapter 1, periods Recognize whether a study is an experiment, survey or observational Section 4.2 (each 85 min) study. Workshop Stats Identify individuals and variables within a data set. Topics 1,2, 3, 6, 7, Classify variables as categorical or quantitative. 8, 9, 10 Make and interpret bar graphs, pie charts, stem plots, dot plots, box plots, histograms and other graphical representations of distributions. Find and interpret numerical measures of center and spread. Describe distributions by their shape, center and spread. Recognize outliers. Comparing distributions using graphical methods. Use a graphing calculator to obtain summary statistics and graphical representations of a data set. Describe the relationship between two categorical variables. Unit 2: The Normal Distribution YMS Chapter 2 10 class Students will be able to: Workshop Stats periods Find and interpret the standardized score of an observation. Topic 12 (each 85 min) Use percentiles to locate individual values within a distribution. Apply Chebyshev’s inequality. Describe the properties of a density curve including the locations of the mean and median depending on the shape. Describe the properties of a normal density curve. Apply the Empirical (68-95-99.7) Rule. Use the normal density curve to calculate the proportion of values in a specified range and to determine a z-score from a percentile. Apply the normal curve to any distribution with mean µ and standard deviation σ. Apply graphical elements to assess the normality of a distribution. Unit 3: Producing Data YMS Chapter 5 8 class Students will be able to: Workshop Stats periods Identify a population in a sampling situation. Topics 4, 5 (each 85 min) Identify different methods of sampling, strengths and weaknesses of each and possible bias that might result. Recognize the difference between an observational study and an experiment. Identify explanatory and response variables. Outline the design of a random experiment. Recognize bias due to confounding of explanatory variables Recognize the placebo effect and when a double-blind technique should be implemented. Explain how to design an experiment to support a cause-and-effect relationship. Unit 4: Probability YMS Chapter 6 12 class Students will be able to: Workshop Stats periods Describe the sample space for random events. Topic 11 (each 85 min) Apply the basic rules of probability. Appropriately use multiplication and addition rules of probability. Identify disjoint, complementary and independent events. Use tree diagrams, Venn diagrams and counting techniques in solving probability problems. Unit 5: Random Variables YMS Chapter 7 12 class Students will be able to: periods Recognize and define discrete and continuous variables. (each 85 min) Find probabilities related to normal random variables. Calculate the mean and variance of discrete random variables. Use simulation methods using the graphing calculator and the law of large numbers to approximate the mean of a distribution. Use rules for means and rules for variances to solve problems involving sums, differences, and linear combinations of random variables. Unit 6: Binomial and Geometric Distributions YMS Chapter 8 6 class periods Students will be able to: (each 85 min) Verify the four conditions of a binomial distribution: two outcomes, fixed number of trials, independent trails, and the same probability of success for each trial. Calculate cumulative distribution functions, cumulative distribution tables and histograms, means and standard deviations of binomial random variables. Use a normal approximation to the binomial distribution to compute probabilities. Verify the four conditions of a geometric distribution: two outcomes, the probability of success for each trial, independent trials, and the count of interest is the number of trials required to get the first success. Calculate cumulative distribution functions, cumulative distribution tables and histograms, means and standard deviations of geometric random variables. Unit 7: Sampling Distributions YMS Chapter 9 10 class Students will be able to: Workshop Stats periods Identify parameters and statistics in a sample. Topics 13, 14, 15 (each 85 min) Interpret a sampling distribution, including bias and variability and how to influence each. Recognize when a problem involves a sample proportion. Analyze problems involving sample proportions, including using the normal distribution to calculate probabilities. Recognize when a problem involves a sample mean. Analyze problems involving sample means and understand how to use the central limit theorem to approximate a normal distribution. Unit 8: Confidence Intervals YMS Chapter 10 10 class Students will be able to: Workshop Stats periods Describe confidence intervals. Topic 16, 19 (each 85 min) Calculate a confidence interval for the mean of a population when the standard deviation is known. Find the sample size required to obtain a confidence interval of specified margin of error. Use the t-procedure to obtain confidence intervals for the mean and recognize when the t interval is appropriate. Use the z-procedure to obtain confidence intervals for a population proportion. Unit 9: Introduction to Significance Tests YMS Chapter 11 8 class Students will be able to: Workshop Stats periods State the null and alternative hypotheses in a testing situation Topics 17, 18, 20 (each 85 min) involving a population mean. Calculate the one-sample z statistics and the P-value for both one- sided and two-sided tests about the mean. Assess statistical significance by comparing values. Explain Type I error, Type II error and power in significance testing. Unit 10: Significance Tests about One Parameter YMS Chapter 12 8 class Students will be able to: Workshop Stats periods Perform and analyze a one-sample t-test to hypothesize a population Topics 17, 18, 20 (each 85 min) mean and discuss the possible problems inherent in the test. Use the z procedure to test significance of a hypothesis about a population proportion. Unit 11: Significance Tests Comparing Two Parameters YMS Chapter 13 8 class Students will be able to: Workshop Stats periods Recognize whether one-sample, matched pairs or two-sample Topics 21, 22, 23 (each 85 min) procedures are needed. Perform and analyze a two-sample t test to compare the difference between two means and discus the possible problems inherent in the test. Use the two-sample z procedure to test the hypothesis regarding equality of proportions in two distinct populations. Unit 12: Chi-Square Procedures YMS Chapter 14 5 class Students will be able to: Workshop Stats periods Choose the appropriate chi-square procedure for a given situation. Topics 24, 25 (each 85 min) Perform chi-square test and calculate the various relevant components. Interpret chi-square results from computer output. Unit 13: Examining Relationships YMS Chapter 3, 12 class Students will be able to: Section 4.3 periods Identify variables as quantitative or categorical. Workshop Stats (each 85 min) Identify explanatory and response variables. Topics 26, 27, 28 Make and analyze scatter plots to assess a relationship between two variables. Find and interpret the correlation coefficient between two variables. Find and analyze regressions lines. Use regression lines to predict values and assess the validity of these predictions. Calculate residuals and use their plots to recognize unusual patterns. Recognize limitations in the correlation coefficient and least squares regression due to extreme values. Recognize lurking variables. Explain the difference between correlation and causation. Unit 14: Inference for Regression YMS Chapter 15, 8 class Students will be able to: Section 4.1 periods Recognize when linear regression is appropriate for a data set. Workshop Stats (each 85 min) Interpret the meaning of a regression for a given data set. Topic 29 Interpret the results of computer output for regression. Recognize exponential growth and decay. Use logarithmic transformations to model a linear pattern, linear regression to find a prediction equation for the linear data, and transform back to a nonlinear model of the original data. Class time (2-3 class periods) will be given for in-class work on each of the four major projects. Additionally, there will be significant class time dedicated to AP Exam review prior to taking the AP Exam.

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AP Statistics, confidence intervals, AP Exam, Sampling Distributions, graphing calculator, random variables, confidence interval, Sampling distribution, Statistical Inference, statistics course

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posted: | 3/9/2011 |

language: | English |

pages: | 4 |

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