2.75: 84% 2.5: 80% 2.25: 78% 2: 74% 1.75: 70% 1.5: 66% 1.25: 64% 1.0: 60% 0.5: 50% 0.25: 25% 0: 0%

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1 Capstone Test (will consist of FOUR quizzes and the FINAL test grade will be an average of the four quizzes). Capstone #1: Review of Chapters 1-3 Capstone #2: Review of Chapter 4 Capstone #3: Review of Chapters 5-7 Capstone #4: Review of Chapters 8-12 GRADING OF CAPSTONE TEST : Suppose you made the following grades: o Capstone #1: 4 o Capstone #2: 5 o Capstone #3: 2 o Capstone #4: 3 FINAL GRADE ON TEST: 3.5 GRADING SCALE OF CAPSTONE TEST : 5: 110% 4.75: 105% 4.5: 100% 4.25: 98% 4.0: 96% 3.75: 94% 3.5: 92% 3.25: 90% 3: 88% 2.75: 84% 2.5: 80% 2.25: 78% 2: 74% 1.75: 70% 1.5: 66% 1.25: 64% 1.0: 60% 0.5: 50% 0.25: 25% 0: 0% HOMEWORK: (Due by May 12 th at Midnight) All HW for remainder of the year will be assigned via Study Island. Assignments will consist of FIVE Multiple Choice Questions per assignment. These assignments will each be scored 0 through 5, dictated by the number of questions a student gets correct. Students will receive a grade equivalent to a test grade and the scoring of these assignments will follow the same guide scoring for the Capstone Tests. (see above) IMPORTANT NOTES: *re-takes allowed on Capstone Tests; Tests will not be handed back after they are taken. *Questions from old tests may be recycled for Capstone Tests *Strive Book, Chapter packets, and Chapter Tests/Re-Tests will be primary source of Exam Preparation *all capstones MUST be taken by the date of the AP Exam.

2 Unit 1 Quiz I can describe a distribution by focusing on the following features: Center, Shape, Spread, Outliers. I can utilize the formula for standardizing to calculate z scores to make comparisons. I can understand how to use a line of best fit (LSRL) to model the relationship between two variables. I can examine the fit of a regression line by studying its residuals. I can interpret the linearity of a relationship between two quantitative by looking at its corresponding residual plot. I can use an LSRL to make predictions. I can identify the locations of the mean and median on a density curve based on whether it is symmetric or skewed. I can understand how to determine whether a distribution is normal and can also identify the key characteristics of a normal curve and how it differs from distributions that are not symmetric shaped. I can identify the locations of the mean and median on a density curve based on whether it is symmetric or skewed. I can understand how to use a normal probability plot to assess the normality of a distribution. I can understand how a transformation of a set of data (changing units of measurement or by adding a constant a to the data) will affect the measures of center and spread, along with the measures of location (quartiles & percentiles). #10. I can calculate a percentile rank by using its general definition (% at OR below the value) and by using skills acquired from: The 5 # summary, Quartiles and IQR % Rule (Empirical Rule) I can detect outliers and influential observations that may or may not significantly affect or change its corresponding correlation and/or regression line. I can interpret a correlation value, as well as the value of the coefficient of determination (r-squared) in the context of a given problem. I can utilize the formula for standardizing to compare two or more values. (via z-score).

3 #14. I can utilize the formula for standardizing to calculate probabilities (via z- scores). #15. I can detect outliers and influential observations that may or may not significantly affect or change its corresponding correlation and/or regression line. I can describe a distribution (OR compare two distributions) by focusing on the following features: Center, Shape, Spread, Outliers. I can interpret the slope and intercept of a regression line in the context of a given problem. I can use an LSRL to make predictions. I can display relationships between two variables appropriately using a scatter plot and can also properly identify and relate an explanatory (x) and response (y) variable. Unit 2 Quiz I can give advantages and disadvantages of each sampling method. I can explain how under coverage, nonresponse, and question wording can lead to bias in a sample survey. I can distinguish between a completely randomized design and a randomized block design. I can describe a completely randomized design for an experiment. I can distinguish between an observational study and an experiment. I can explain how under coverage, nonresponse, and question wording can lead to bias in a sample survey. I can explain how these bad sampling methods can lead to bias. I can explain how under coverage, nonresponse, and question wording can lead to bias in a sample survey. I can explain how these bad sampling methods can lead to bias. I can explain how a lurking variable in an observational study can lead to confounding. I can distinguish a simple random sample from a stratified random sample. I can distinguish between a completely randomized design and a randomized block design. I can give advantages and disadvantages of each sampling method.

4 #10. I can determine the scope of inference for a statistical study. I can identify a cluster or multi-stage sample and distinguish them from simple random or stratified samples. I can determine the scope of inference for a statistical study. I can calculate a percentile rank by using its general definition (% at OR below the value) and by using skills acquired from: o The 5 # summary, Quartiles and IQR #14. I can identify the locations of the mean and median on a density curve based on whether it is symmetric or skewed. #15. I can interpret a correlation value, as well as the value of the coefficient of determination (r-squared) in the context of a given problem. I can identify the experimental units or subjects, explanatory variables (factors), treatments, and response variables in an experiment. I can identify a cluster or multi-stage sample and distinguish them from simple random or stratified samples. I can distinguish a simple random sample from a stratified random sample. Unit 3 Quiz I can, when appropriate, use the multiplication rule for independent events to compute probabilities. I can use a probability distribution to answer questions about possible values of a random variable. I can describe a probability model for a chance process. I can find the probability that an event occurs using a two-way table. I can find the mean and standard deviation of the sum or difference of independent random variables. I can use the general addition rule to calculate P(A B) I can determine whether two events are independent. I can use basic probability rules, including the complement rule and the addition rule for mutually exclusive events. I can use a probability distribution to answer questions about possible values of a random variable. I can interpret the standard deviation of a random variable in context. I can describe the effects of transforming a random variable by adding or

5 subtracting a constant and multiplying or dividing by a constant. I can find the mean and standard deviation of the sum or difference of independent random variables. I can use basic probability rules, including the complement rule and the addition rule for mutually exclusive events. I can use the general multiplication rule to solve probability questions. I can determine whether two events are independent. I can, when appropriate, use the multiplication rule for independent events to compute probabilities. #10. I can find the probability that an event occurs using a two-way table. I can calculate the mean of a discrete random variable. I can interpret the mean of a random variable in context. I can calculate probabilities involving a sample mean x when the population distribution is Normal. I can compute conditional probabilities. #14. I can explain how the shape of the sampling distribution of x is related to the shape of the population distribution. I can check whether the 10% and Normal conditions are met in a given setting. I can find the mean and standard deviation of the sampling distribution of a sample mean x from an SRS of size n. I can determine whether a statistic is an unbiased estimator of a population parameter. #15. I can use the central limit theorem to help find probabilities involving a sample mean x. I can determine whether a statistic is an unbiased estimator of a population parameter. I can understand the relationship between sample size and the variability of an estimator. #16. I can determine whether the conditions for a binomial random variable are met. I can find the mean and standard deviation of the sampling distribution of a sample mean x from an SRS of size n. I can calculate probabilities involving a sample mean x when the population distribution is Normal. I can calculate the mean of a discrete random variable.

6 Unit 4 Quiz I can understand how confidence level or sample size will affect the margin of error. I can interpret a confidence level and interval in context. I can correctly interpret the meaning of the margin of error in context. I can identify a point estimator to help estimate an unknown parameter. I can carry out the steps in constructing a confidence interval for a population mean: define the parameter; check conditions; perform calculations; interpret results in context. I can construct and interpret a confidence interval for a population proportion or mean. I can construct and interpret a confidence interval for a population proportion or mean. I can determine the sample size required to obtain a level C confidence interval for a population proportion or mean with a specified margin of error. I can recognize paired data and use one-sample t procedures to perform significance tests for such data. I can interpret P-values in context. I can interpret P-values in context. #10. I can recognize paired data and use one-sample t procedures to perform significance tests for such data. I can determine the proper inference procedure to use in a given setting. I can construct and interpret a confidence interval for the slope β of the population regression line. I can state correct hypotheses for a significance test about a population proportion or mean. I can state correct hypotheses for a significance test about a population proportion or mean. #14. I can state correct hypotheses for a significance test about a population proportion or mean. I can interpret P-values in context. I can interpret a Type I error and a Type II error in context, and give the consequences of each. I can use a chi-square goodness-of-fit test to determine whether sample data are consistent with a specified distribution of a categorical variable.