ࡱ> D bjbj$$ ;F|F|%vv8x"r?,k$~08"8"8"*%*%*%8"*%8"*%*%F͝p! "Tqְ0ж#6ж͝ж͝,*% 1!$p8"8"8"8"жv : AP Statistics Syllabus COURSE DESCRIPTION: AP Statistics is the high school equivalent of a one semester, introductory college statistics course. In this course, students develop strategies for collecting, organizing, analyzing, and drawing conclusions from data. Students design, administer, and tabulate results from surveys and experiments. Probability and simulations aid students in constructing models for chance behavior. Sampling distributions provide the logical structure for confidence intervals and hypothesis tests. Students use a TI-83/84 graphing calculator, Fathom and Minitab statistical software, and Web-based java applets to investigate statistical concepts. To develop effective statistical communication skills, students are required to prepare frequent written and oral analyses of real data. COURSE GOALS: In AP Statistics, students are expected to learn Skills To produce convincing oral and written statistical arguments, using appropriate terminology, in a variety of applied settings. When and how to use technology to aid them in solving statistical problems Knowledge Essential techniques for producing data (surveys, experiments, observational studies), analyzing data (graphical & numerical summaries), modeling data (probability, random variables, sampling distributions), and drawing conclusions from data (inference procedures confidence intervals and significance tests) Habits of mind To become critical consumers of published statistical results by heightening their awareness of ways in which statistics can be improperly used to mislead, confuse, or distort the truth. COURSE OUTLINE: Text: The Practice of Statistics (4th edition), by Starnes, Yates, and Moore, W. H. Freeman & Co., 2010. Chapter 1 DayTopicsObjectives: Students will be able toHomework1Chapter 1 Introduction; Activity: Hiring discrimination: This activity models the components of the statistical problem solving process: research question, data analysis, probability model, and inferenceIdentify the individuals and variables in a set of data. Classify variables as categorical or quantitative. Identify units of measurement for a quantitative variable.1, 3, 5, 7, 821.1 Bar Graphs and Pie Charts, Graphs: Good and BadMake a bar graph of the distribution of a categorical variable or, in general, to compare related quantities. Recognize when a pie chart can and cannot be used. Identify what makes some graphs deceptive.11, 13, 15, 1731.1 Two-Way Tables and Marginal Distributions, Relationships Between Categorical Variables: Conditional Distributions, Organizing a Statistical Problem, Technology: Analyzing Two-Way Tables with MinitabFrom a two-way table of counts, answer questions involving marginal and conditional distributions. Describe the relationship between two categorical variables in context by comparing the appropriate conditional distributions. Construct bar graphs to display the relationship between two categorical variables. 19, 21, 23, 25, 27-3241.2 Dotplots, Describing Shape, Comparing Distributions, StemplotsMake a dotplot or stemplot to display small sets of data. Describe the overall pattern (shape, center, spread) of a distribution and identify any major departures from the pattern (like outliers). Identify the shape of a distribution from a dotplot, stemplot, or histogram as roughly symmetric or skewed. Identify the number of modes. 37, 39, 41, 43, 45, 4751.2 Histograms, Using Histograms Wisely, Technology: Making Histograms on the CalculatorMake a histogram with a reasonable choice of classes. Identify the shape of a distribution from a dotplot, stemplot, or histogram as roughly symmetric or skewed. Identify the number of modes. Interpret histograms.53, 55, 57, 59, 60, 69-7461.3 Measuring Center: Mean and Median, Comparing Mean and Median, Measuring Spread: IQR, Identifying OutliersCalculate and interpret measures of center (mean, median) in context Calculate and interpret measures of spread (IQR) in context Identify outliers using the 1.5 ( IQR rule.79, 81, 83, 87, 8971.3 Five Number Summary and Boxplots, Measuring Spread: Standard Deviation, Choosing Measures of Center and Spread, Technology: Making Boxplots on the Calculator, Computing Numerical Summaries with Minitab and the CalculatorMake a boxplot. Calculate and interpret measures of spread (standard deviation) Select appropriate measures of center and spread Use appropriate graphs and numerical summaries to compare distributions of quantitative variables. 91, 93, 95, 97, 103, 105, 107-1108Chapter 1 ReviewChapter 1 Review Exercises9Chapter 1 Test Chapter 1 Project: Critical statistical analysis each student collects data and analyzes it using the techniques learned in this unit and prepares a written analysis. Evaluation using a four-point rubric like the AP Free Response questions. Chapter 2 DayTopicsObjectives: Students will be able toHomework12.1 Introduction, Measuring Position: Percentiles, Cumulative Relative Frequency Graphs, Measuring Position: z-scores Use percentiles to locate individual values within distributions of data. Interpret a cumulative relative frequency graph. Find the standardized value (z-score) of an observation. Interpret z-scores in context.5, 7, 9, 11, 13, 1522.1 Transforming Data, Density CurvesDescribe the effect of adding, subtracting, multiplying by, or dividing by a constant on the shape, center, and spread of a distribution of data. Approximately locate the median (equal-areas point) and the mean (balance point) on a density curve.19, 21, 23, 31, 33-3832.2 Normal Distributions, The 68-95-99.7 Rule, The Standard Normal Distribution, Technology: Standard Normal Curve Calculations with the Calculator and with an AppletUse the 689599.7 rule to estimate the percent of observations from a Normal distribution that fall in an interval involving points one, two, or three standard deviations on either side of the mean. Use the standard Normal distribution to calculate the proportion of values in a specified interval. Use the standard Normal distribution to determine a z-score from a percentile.41, 43, 45, 47, 49, 5142.2 Normal Distribution Calculations, Technology: Normal Curve Calculations with the Calculator and with an AppletUse Table A to find the percentile of a value from any Normal distribution and the value that corresponds to a given percentile.53, 55, 57, 5952.2 Assessing Normality, Normal Probability Plots on the CalculatorMake an appropriate graph to determine if a distribution is bell-shaped. Use the 68-95-99.7 rule to assess Normality of a data set. Interpret a Normal probability plot63, 65, 66, 68, 69-746Chapter 2 ReviewChapter 2 Review Exercises7Chapter 2 Test39R, 40R, 75R, 76R Chapter 3 DayTopicsObjectives: Students will be able to Homework1Chapter 3 Introduction, Activity: CSI Stats, 3.1 Explanatory and response variables, 3.1 Displaying relationships: scatterplots, 3.1 Interpreting scatterplots, Technology: Scatterplots on the CalculatorDescribe why it is important to investigate relationships between variables. 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. Describe the direction, form, and strength of the overall pattern of a scatterplot. Recognize outliers in a scatterplot.1, 5, 7, 11, 1323.1 Measuring linear association: correlation, 3.1 Facts about correlation, Technology: Correlation and Regression AppletKnow the basic properties of correlation. Calculate and interpret correlation in context. Explain how the correlation r is influenced by extreme observations.1418, 21, 2633.2 Least-squares regression, 3.2 Interpreting a regression line, 3.2 Prediction, Technology: Least-Squares Regression Lines on the CalculatorInterpret the slope and y intercept of a least-squares regression line in context. Use the least-squares regression line to predict y for a given x. Explain the dangers of extrapolation.2732, 35, 37, 39, 4143.2 Residuals and the least-squares regression line, 3.2 Calculating the equation of the least-squares regression line, Technology: Residual Plots and s on the CalculatorCalculate and interpret residuals in context. Explain the concept of least squares. Use technology to find a least-squares regression line. Find the slope and intercept of the least-squares regression line from the means and standard deviations of x and y and their correlation.43, 45, 47, 5353.2 How well the line fits the data: residual plots, 3.2 How well the line fits the data: the role of r2 in regressionConstruct and interpret residual plots to assess if a linear model is appropriate. Use the standard deviation of the residuals to assess how well the line fits the data. Use r2 to assess how well the line fits the data. Interpret the standard deviation of the residuals and r2 in context.49, 54, 56, 586163.2 Interpreting computer regression output, 3.2 Correlation and regression wisdom, Technology: Least-Squares Regression using Minitab and JMPIdentify the equation of a least-squares regression line from computer output. Explain why association doesnt imply causation. Recognize how the slope, y intercept, standard deviation of the residuals, and r2 are influenced by extreme observations.63, 65, 68, 69, 71787Chapter 3 ReviewChapter Review Exercises8Chapter 3 Test33R, 34R, 79R, 80R, 81R Chapter 4 DayTopicsObjectives: Students will be able toHomework14.1 Introduction, Sampling and Surveys, How to Sample Badly, How to Sample Well: Random Samples, Technology: Choosing an SRS using an Applet or CalculatorIdentify the population and sample in a sample survey. Identify voluntary response samples and convenience samples. Explain how these bad sampling methods can lead to bias. Describe how to use Table D to select a simple random sample (SRS).1, 3, 5, 7, 9, 1124.1 Other Sampling MethodsDistinguish a simple random sample from a stratified random sample or cluster sample. Give advantages and disadvantages of each sampling method.17, 19, 21, 23, 2534.1 Inference for Sampling, Sample Surveys: What Can Go Wrong?Explain how undercoverage, nonresponse, and question wording can lead to bias in a sample survey.27, 28, 29, 31, 33, 3544.2 Observational Studies vs. Experiments, The Language of Experiments, How to Experiment BadlyDistinguish between an observational study and an experiment. Explain how a lurking variable in an observational study can lead to confounding. Identify the experimental units or subjects, explanatory variables (factors), treatments, and response variables in an experiment.37-42, 45, 47, 49, 51, 5354.2 How to Experiment Well, Three Principles of Experimental DesignDescribe a completely randomized design for an experiment. Explain why random assignment is an important experimental design principle. 57, 63, 65, 6764.2 Experiments: What Can Go Wrong? Inference for ExperimentsDescribe how to avoid the placebo effect in an experiment. Explain the meaning and the purpose of blinding in an experiment. Explain in context what statistically significant means.69, 71, 73, 75* (*We will analyze this data again in an Activity in chapter 10)74.2 Blocking, Matched Pairs DesignDistinguish between a completely randomized design and a randomized block design. Know when a matched pairs experimental design is appropriate and how to implement such a design.77, 79, 81, 85, 84.3 Scope of Inference, the Challenges of Establishing CausationDetermine the scope of inference for a statistical study.91-98, 102-10894.2 Class Experiments or 4.3 Data Ethics* (*optional topic)Evaluate whether a statistical study has been carried out in an ethical manner.55, 83, 87, 8910Chapter 4 ReviewChapter 4 Review Exercises11Chapter 4 TestPart 1: Cumulative AP Review Exercises Chapter 4 Project: Students work in teams of 2 to design and carry out an experiment to investigate response bias, write a summary report, and give a 10 minute oral synopsis to their classmates. See rubric on page 15. Chapter 5 DayTopicsObjectives: Students will be able toHomework15.1 Introduction, The Idea of Probability, Myths about RandomnessInterpret probability as a long-run relative frequency in context. 1, 3, 7, 9, 1125.1 Simulation, Technology: Random Numbers with CalculatorsUse simulation to model chance behavior.15, 17, 19, 23, 2535.2 Probability Models, Basic Rules of ProbabilityDescribe a probability model for a chance process. Use basic probability rules, including the complement rule and the addition rule for mutually exclusive events.27, 31, 32, 43, 45, 4745.2 Two-Way Tables and Probability, Venn Diagrams and ProbabilityUse a Venn diagram to model a chance process involving two events. Use the general addition rule to calculate P(A EMBED Equation.DSMT4 B)29, 33-36, 49, 51, 53, 5555.3 What is Conditional Probability?, Conditional Probability and Independence, Tree Diagrams and the General Multiplication RuleWhen appropriate, use a tree diagram to describe chance behavior. Use the general multiplication rule to solve probability questions. Determine whether two events are independent. Find the probability that an event occurs using a two-way table.57-60, 63, 65, 67, 69, 73, 77, 79 65.3 Independence: A Special Multiplication Rule, Calculating Conditional ProbabilitiesWhen appropriate, use the multiplication rule for independent events to compute probabilities. Compute conditional probabilities.83, 85, 87, 91, 93, 95, 97, 997ReviewChapter 5 Review Problems8Chapter 5 Test61R, 62R, 107R, 108R, 109R Chapter 6 DayTopicsObjectives: Students will be able toHomework1Chapter 6 Introduction, 6.1 Discrete random Variables, Mean (Expected Value) of a Discrete Random VariableUse a probability distribution to answer questions about possible values of a random variable. Calculate the mean of a discrete random variable. Interpret the mean of a random variable in context.1, 5, 7, 9, 1326.1 Standard Deviation (and Variance) of a Discrete Random Variable, Continuous Random Variables, Technology: Analyzing Random Variables on the CalculatorCalculate the standard deviation of a discrete random variable. Interpret the standard deviation of a random variable in context. 14, 18, 19, 23, 2536.2 Linear TransformationsDescribe the effects of transforming a random variable by adding or subtracting a constant and multiplying or dividing by a constant.27-30, 37, 39-41, 43, 4546.2 Combining Random Variables, Combining Normal Random VariablesFind the mean and standard deviation of the sum or difference of independent random variables. Determine whether two random variables are independent. Find probabilities involving the sum or difference of independent Normal random variables.49, 51, 57-59, 6356.3 Binomial Settings and Binomial Random Variables, Binomial Probabilities, Technology: Binomial Probabilities on the CalculatorDetermine whether the conditions for a binomial random variable are met. Compute and interpret probabilities involving binomial distributions.61, 65, 66, 69, 71, 73, 75, 7766.3 Mean and Standard Deviation of a Binomial Distribution, Binomial Distributions in Statistical SamplingCalculate the mean and standard deviation of a binomial random variable. Interpret these values in context.79, 81, 83, 85, 87, 8976.3 Geometric Random Variables, Technology: Geometric Probabilities on the CalculatorFind probabilities involving geometric random variables.93, 95, 97, 99, 101-1038Chapter 6 ReviewChapter 6 Review Exercises9Chapter 6 Test31R-34R EXAM REVIEW: 3 DAYS SEMESTER 1 EXAM: Simulated AP format with Multiple Choice, Free Response Chapter 7 DayTopicsObjectives: Students will be able toHomework1Introduction: German Tank Problem, 7.1 Parameters and Statistics, Technology: Using Fathom to Simulate Sampling DistributionsDistinguish between a parameter and a statistic.1, 3, 5, 727.1 Sampling Variability, Describing Sampling DistributionsUnderstand the definition of a sampling distribution. Distinguish between population distribution, sampling distribution, and the distribution of sample data. Determine whether a statistic is an unbiased estimator of a population parameter. Understand the relationship between sample size and the variability of an estimator.9, 11, 13, 17-2037.2 The Sampling Distribution of  EMBED Equation.DSMT4 , Using the Normal Approximation for  EMBED Equation.DSMT4 , Technology: Using an Applet to Simulate the distribution of  EMBED Equation.DSMT4 . Find the mean and standard deviation of the sampling distribution of a sample proportion  EMBED Equation.DSMT4  for an SRS of size n from a population having proportion p of successes. Check whether the 10% and Normal conditions are met in a given setting. Use Normal approximation to calculate probabilities involving  EMBED Equation.DSMT4 . Use the sampling distribution of  EMBED Equation.DSMT4  to evaluate a claim about a population proportion.21-24, 27, 29, 33, 35, 37, 4147.3 The Sampling Distribution of  EMBED Equation.DSMT4 : Mean and Standard Deviation, Sampling from a Normal Population, Technology: Using an Applet to Simulate the distribution of  EMBED Equation.DSMT4 . Find the mean and standard deviation of the sampling distribution of a sample mean  EMBED Equation.DSMT4  from an SRS of size n. Calculate probabilities involving a sample mean  EMBED Equation.DSMT4  when the population distribution is Normal.43-46, 49, 51, 53, 5557.3 The Central Limit TheoremExplain how the shape of the sampling distribution of  EMBED Equation.DSMT4  is related to the shape of the population distribution. Use the central limit theorem to help find probabilities involving a sample mean  EMBED Equation.DSMT4 .57, 59, 61, 63, 65-686Chapter 7 ReviewChapter 7 Review Exercises7Chapter 7 Test69R-72R Chapter 8 DayTopicsObjectives: Students will be able to:Homework18.1 The Idea of a Confidence Interval, Interpreting Confidence Levels and Confidence Intervals, Constructing a Confidence Interval, Technology: Simulating Confidence Intervals with the Confidence Interval AppletInterpret a confidence level in context. Interpret a confidence interval in context. Understand that a confidence interval gives a range of plausible values for the parameter.5, 7, 9, 11, 1328.1 Using Confidence Intervals Wisely, 8.2 Conditions for Estimating p, Constructing a Confidence Interval for pUnderstand why each of the three inference conditionsRandom, Normal, and Independentis important. Explain how practical issues like nonresponse, undercoverage, and response bias can affect the interpretation of a confidence interval. Construct and interpret a confidence interval for a population proportion. Determine critical values for calculating a confidence interval using a table or your calculator.17, 1924, 27, 31, 3338.2 Putting It All Together: The Four-Step Process, Choosing the Sample Size, Technology: Confidence Intervals for p on the CalculatorCarry out the steps in constructing a confidence interval for a population proportion: define the parameter; check conditions; perform calculations; interpret results in context. Determine the sample size required to obtain a level C confidence interval for a population proportion with a specified margin of error. Understand how the margin of error of a confidence interval changes with the sample size and the level of confidence C. Understand why each of the three inference conditionsRandom, Normal, and Independentis important.35, 37, 41, 43, 4748.3 When  EMBED Equation.DSMT4  Is Known: The One-Sample z Interval for a Population Mean, When  EMBED Equation.DSMT4  Is Unknown: The t Distributions, Constructing a Confidence Interval for  EMBED Equation.DSMT4 , Technology: Inverse t on the CalculatorConstruct and interpret a confidence interval for a population mean. Determine the sample size required to obtain a level C confidence interval for a population mean with a specified margin of error. Carry out the steps in constructing a confidence interval for a population mean: define the parameter; check conditions; perform calculations; interpret results in context.4952, 55, 57, 59, 6358.3 Using t Procedures Wisely, Technology: Confidence Intervals for  EMBED Equation.DSMT4  on the CalculatorUnderstand why each of the three inference conditionsRandom, Normal, and Independentis important.65, 67, 71, 73, 75786Chapter 8 ReviewDetermine sample statistics from a confidence interval.Chapter 8 Review Exercises7Chapter 8 Test Chapter 9 DayTopicsObjectives: Students will be able to:Homework19.1 The Reasoning of Significance Tests, Stating Hypotheses, Interpreting P-values, Statistical SignificanceState correct hypotheses for a significance test about a population proportion or mean. Interpret P-values in context.1, 3, 5, 7, 9, 11, 1329.1 Type I and Type II Errors, Planning Studies: The Power of a Statistical Test, Technology: Investigating Power with an AppletInterpret a Type I error and a Type II error in context, and give the consequences of each. Understand the relationship between the significance level of a test, P(Type II error), and power.15, 19, 21, 23, 2539.2 Carrying Out a Significance Test, The One-Sample z Test for a Proportion, Technology: One-Proportion z Test on the CalculatorCheck conditions for carrying out a test about a population proportion. If conditions are met, conduct a significance test about a population proportion.2730, 41, 43, 4549.2 Two-Sided Tests, Why Confidence Intervals Give More Information, Technology: Tests and Confidence Intervals using MinitabUse a confidence interval to draw a conclusion for a two-sided test about a population proportion.47, 49, 51, 53, 5559.3 Carrying Out a Significance Test for  EMBED Equation.DSMT4 , The One Sample t Test, Two-Sided Tests and Confidence Intervals, Technology: Computing P-values from t Distributions on the Calculator, One Sample t Test on the CalculatorCheck conditions for carrying out a test about a population mean. If conditions are met, conduct a one-sample t test about a population mean  EMBED Equation.DSMT4 . Use a confidence interval to draw a conclusion for a two-sided test about a population mean.5760, 71, 7369.3 Inference for Means: Paired Data, Using Tests WiselyRecognize paired data and use one-sample t procedures to perform significance tests for such data. 75, 77, 89, 9497, 991047Chapter 9 ReviewChapter 9 Review Exercises8Chapter 9 Test Chapter 10 DayTopicsObjectives: Students will be able toHomework1Activity: Is Yawning Contagious?, 10.1 The Sampling Distribution of a Difference Between Two ProportionsDescribe the characteristics of the sampling distribution of  EMBED Equation.DSMT4  Calculate probabilities using the sampling distribution of  EMBED Equation.DSMT4 1, 3, 5210.1 Confidence Intervals for p1 p2 , Technology: Confidence Intervals for a Difference in Proportions on the CalculatorDetermine whether the conditions for performing inference are met. Construct and interpret a confidence interval to compare two proportions.7, 9, 11, 13310.1 Significance Tests for p1 p2, Inference for Experiments, Technology: Significance Tests for a Difference in Proportions on the CalculatorPerform a significance test to compare two proportions. Interpret the results of inference procedures in a randomized experiment.15, 17, 21, 23410.2 Activity: Does Polyester Decay?, The Sampling Distribution of a Difference Between Two MeansDescribe the characteristics of the sampling distribution of  EMBED Equation.DSMT4  Calculate probabilities using the sampling distribution of  EMBED Equation.DSMT4 29-32, 35, 37, 57510.2 The Two-Sample t-Statistic, Confidence Intervals for  EMBED Equation.DSMT4 , Technology: Confidence Intervals for a Difference in Means on the CalculatorDetermine whether the conditions for performing inference are met. Use two-sample t procedures to compare two means based on summary statistics. Use two-sample t procedures to compare two means from raw data. Interpret standard computer output for two-sample t procedures.39, 41, 43, 45610.2 Significance Tests for  EMBED Equation.DSMT4 , Using Two-Sample t Procedures Wisely, Technology: Two Sample t Tests with Computer Software and CalculatorsPerform a significance test to compare two means. Check conditions for using two-sample t procedures in a randomized experiment. Interpret the results of inference procedures in a randomized experiment. 51, 53, 59, 65, 67-707Chapter 10 ReviewDetermine the proper inference procedure to use in a given setting.Chapter 10 Review Exercises8Chapter 10 Test33R, 34 R, 75 R, 76 R Chapter 11 DayTopicsObjectives: Students will be able toHomework1Activity: The Candy Man Can, 11.1 Comparing Observed and Expected Counts: The Chi-Square Statistic, The Chi-Square Distributions and P-values, Technology: Finding P-values for Chi-Square Tests on the CalculatorKnow how to compute expected counts, conditional distributions, and contributions to the chi-square statistic.1, 3, 5211.1 The Chi-Square Goodness-of-Fit Test, Follow-Up Analysis, Technology: Chi-Square Goodness-of-Fit Tests on the CalculatorCheck the Random, Large sample size, and Independent conditions before performing a chi-square test. Use a chi-square goodness-of-fit test to determine whether sample data are consistent with a specified distribution of a categorical variable. Examine individual components of the chi-square statistic as part of a follow-up analysis.7, 9, 11, 17311.2 Comparing Distributions of a Categorical Variable, Expected Counts and the Chi-Square Statistic, The Chi-Square Test for Homogeneity, Follow-Up Analysis, Comparing Several Proportions, Technology: Chi-Square Tests for Two-Way Tables with Computer Software and CalculatorsCheck the Random, Large sample size, and Independent conditions before performing a chi-square test. Use a chi-square test for homogeneity to determine whether the distribution of a categorical variable differs for several populations or treatments. Interpret computer output for a chi-square test based on a two-way table. Examine individual components of the chi-square statistic as part of a follow-up analysis. Show that the two-sample z test for comparing two proportions and the chi-square test for a 2-by-2 two-way table give equivalent results.19-22, 27, 29, 31, 33, 35, 43411.2 The Chi-Square Test of Association/Independence, Using Chi-Square Tests WiselyCheck the Random, Large sample size, and Independent conditions before performing a chi-square test. Use a chi-square test of association/independence to determine whether there is convincing evidence of an association between two categorical variables. Interpret computer output for a chi-square test based on a two-way table. Examine individual components of the chi-square statistic as part of a follow-up analysis.45, 49, 51, 53-585Chapter 11 ReviewDistinguish between the three types of chi-square tests.Chapter 11 Review Exercises6Chapter 11 Test59R, 60R Chapter 12 DayTopicsObjectives: Students will be able toHomework1Activity: The Helicopter Experiment, 12.1 The Sampling Distribution of b, Conditions for Regression InferenceCheck conditions for performing inference about the slope  EMBED Equation.DSMT4  of the population regression line.1, 3212.1 Estimating Parameters, Constructing a Confidence Interval for the Slope, Technology: Regression Inference using Computer Software and CalculatorsInterpret computer output from a least-squares regression analysis. Construct and interpret a confidence interval for the slope  EMBED Equation.DSMT4  of the population regression line.5, 7, 9, 11312.1 Performing a Significance Test for the SlopePerform a significance test about the slope  EMBED Equation.DSMT4  of a population regression line.13, 15, 17, 19412.2 Transforming with Powers and Roots, Technology: Transforming to Achieve Linearity on the CalculatorUse transformations involving powers and roots to achieve linearity for a relationship between two variables. Make predictions from a least-squares regression line involving transformed data.21-26, 33, 35512.2 Transforming with LogarithmsUse transformations involving logarithms to achieve linearity for a relationship between two variables. Make predictions from a least-squares regression line involving transformed data. Determine which of several transformations does a better job of producing a linear relationship. 37, 39, 41, 45-486Chapter 12 ReviewChapter 12 Review Exercises7Chapter 12 TestCumulative AP Practice Test 4 AP EXAM REVIEW (10 days) Practice AP Free Response Questions Choosing the Correct Inference Procedure Mock Grading Sessions Rubric development by student teams Practice Multiple Choice Questions AP STATISTICS EXAM (1 DAY) AFTER THE AP EXAM: FINAL PROJECT (See rubric on page 16) Purpose: The purpose of this project is for you to actually do statistics. You are to form a hypothesis, design a study, conduct the study, collect the data, describe the data, and make conclusions using the data. You are going to do it all!! Topics: You may do your study on any topic, but you must be able to do all 6 steps listed above. Make it interesting and note that degree of difficulty is part of the grade. Group Size: You may work alone or with a partner for this project. Proposal (20 points): To get your project approved, you must be able to demonstrate how your study will meet the requirements of the project. In other words, you need to clearly and completely communicate your hypotheses, your explanatory and response variables, the test/interval you will use to analyze the results, and how you will collect the data so the conditions for inference will be satisfied. You must also make sure that your study will be safe and ethical if you are using human subjects. This should be typed. If your proposal isnt approved, you must resubmit the proposal for partial credit until it is approved. Poster (80 points): The key to a good statistical poster is communication and organization. Make sure all components of the poster are focused on answering the question of interest and that statistical vocabulary is used correctly. The poster should include: Title (in the form of a question). Introduction. In the introduction you should discuss what question you are trying to answer, why you chose this topic, what your hypotheses are, and how you will analyze your data. Data Collection. In this section you will describe how you obtained your data. Be specific. Graphs, Summary Statistics and the Raw Data (if numerical). Make sure the graphs are well labeled, easy to compare, and help answer the question of interest. You should include a brief discussion of the graphs and interpretations of the summary statistics. Discussion and Conclusions. In this section, you will state your conclusion (with the name of the test, test statistic and P-value) and you should discuss why your inference procedure is valid. You should also discuss any errors you made, what you could do to improve the study next time, and any other critical reflections Live action pictures of your data collection in progress. Presentation: Each individual will be required to give a 5 minute oral presentation to the class. RUBRIC FOR CHAPTER 4 PROJECT: Chapter 4 Project4 = Complete3 = Substantial2 = Developing1 = MinimalIntroductionDescribes the context of the research Has a clearly stated question of interest Provides a hypothesis about the answer to the question of interest Question of interest is of appropriate difficultyIntroduces the context of the research and has a specific question of interest Suggests hypothesis OR has appropriate difficultyIntroduces the context of the research and has a specific question of interest OR has question of interest and a hypothesisBriefly describes the context of the researchData CollectionMethod of data collection is clearly described Includes appropriate randomization Describes efforts to reduce bias, variability, confounding Quantity of data collected is appropriateMethod of data collection is clearly described Some effort is made to incorporate principles of good data collection Quantity of data is appropriateMethod of data collection is described Some effort is made to incorporate principles of good data collectionSome evidence of data collectionGraphs and Summary StatisticsAppropriate graphs are included (to help answer the question of interest) Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are included Summary statistics are discussed and correctly interpretedAppropriate graphs are included (to help answer the question of interest) Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are includedGraphs and summary statistics are includedGraphs or summary statistics are includedConclusions Uses the results of the study to correctly answer question of interest Discusses what inferences are appropriate based on study design Shows good evidence of critical reflection (discusses possible errors, shortcomings, limitations, alternate explanations, etc.)Makes a correct conclusion Discusses what inferences are appropriate Shows some evidence of critical reflectionMakes a partially correct conclusion Shows some evidence of critical reflectionMakes a conclusionOverall Presentation/ Communi-cation Clear, holistic understanding of the project Poster is well organized, neat and easy to read Statistical vocabulary is used correctly Poster is visually appealingClear, holistic understanding of the project Statistical vocabulary is used correctly Poster is unorganized or isnt visually appealing,Poster is not well done or communication is poorCommuni-cation and organi-zation are very poor RUBRIC FOR FINAL PROJECT: Final Project4 = Complete3 = Substantial2 = Developing1 = MinimalIntroductionDescribes the context of the research Has a clearly stated question of interest Clearly defines the parameter of interest and states correct hypotheses Question of interest is of appropriate difficultyIntroduces the context of the research and has a specific question of interest Has correct parameter/ hypotheses OR has appropriate difficultyIntroduces the context of the research and has a specific question of interest OR has question of interest and hypotheses Briefly describes the context of the researchData CollectionMethod of data collection is clearly described Includes appropriate randomization Describes efforts to reduce bias, variability, confounding Quantity of data collected is appropriateMethod of data collection is clearly described Some effort is made to incorporate principles of good data collection Quantity of data is appropriateMethod of data collection is described Some effort is made to incorporate principles of good data collectionSome evidence of data collectionGraphs and Summary StatisticsAppropriate graphs are included (to help answer the question of interest) Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are included Summary statistics are discussed and correctly interpretedAppropriate graphs are included (to help answer the question of interest) Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are includedGraphs and summary statistics are includedGraphs or summary statistics are includedAnalysisCorrect inference procedure is chosen Use of inference procedure is justified Test statistic/p-value or confidence interval is calculated correctly p-value or confidence interval is interpreted correctlyCorrect inference procedure is chosen Lacks justification, lacks interpretation, or makes a calculation errorCorrect inference procedure is chosen Test statistic/p-value or confidence interval is calculated correctlyInference procedure is attemptedConclusions Uses p-value/confidence interval to correctly answer question of interest Discusses what inferences are appropriate based on study design Shows good evidence of critical reflection (discusses possible errors, shortcomings, limitations, alternate explanations, etc.)Makes a correct conclusion Discusses what inferences are appropriate Shows some evidence of critical reflectionMakes a partially correct conclusion (such as accepting null). 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