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Statistics · AP · High school · Math

All Course and Exam Description units and topics for Statistics · AP. Topics marked with an asterisk (*) are assessed on the AP Exam; unmarked topics are course scope only. Click a topic for details and future study materials.

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Unit 1: Exploring One-Variable Data

  • 1.1 * Introducing Statistics: What Can We Learn from Data? VAR-1
  • 1.2 * The Language of Variation: Variables VAR-1 Given that variation may be random or not, conclusions are uncertain.
  • 1.3 * Representing a Categorical Variable with Tables UNC-1
  • 1.4 * Representing a Categorical Variable with Graphs UNC-1
  • 1.5 * Representing a Quantitative Variable with Graphs UNC-1
  • 1.6 * Describing the Distribution of a Quantitative Variable UNC-1
  • 1.7 * Summary Statistics for a Quantitative Variable UNC-1 Graphical representations and statistics allow us to identify and represent key
  • 1.8 * Graphical Representations of Summary Statistics UNC-1
  • 1.9 * Comparing Distributions of a Quantitative Variable UNC-1
  • 1.10 * The Normal Distribution VAR-2 The normal distribution can be used to represent some population distributions.

Unit 2: Exploring Two-Variable Data

  • 2.1 * Identify questions to be answered about possible relationships in data.
  • 2.2 * Compare numerical and graphical representations for two categorical variables.
  • 2.3 * Calculate statistics for two categorical variables.
  • 2.4 * Represent bivariate quantitative data using scatterplots.
  • 2.5 * Determinethecorrelation for a linear relationship.
  • 2.6 * Calculate a predicted response value using a linear regression model.
  • 2.7 * Residuals DAT-1 Regression models may allow us to predict responses to changes in an explanatory variable.
  • 2.8 * Estimate parameters for the least-squaresregression line model.
  • 2.9 * Identifyinfluentialpoints in regression.

Unit 3: Collecting Data

  • 3.1 * Identify questions to be answered about data collection methods.
  • 3.2 * Identify the type of a study.
  • 3.3 * Identify a sampling method, given a description of a study.
  • 3.4 * Identify potential sources of bias in sampling methods.
  • 3.5 * Identify the components of an experiment.
  • 3.6 * Explain why a particular experimental design is appropriate.
  • 3.7 * Interpret the results of a well-designedexperiment.

Unit 4: Probability, Random Variables, and Probability Distributions

  • 4.1 * Identify questions suggested by patterns in data.
  • 4.2 * Estimate probabilities using simulation.
  • 4.3 * Calculate probabilities for events and their complements.
  • 4.4 * Explain why two events are (or are not) mutually exclusive.
  • 4.5 * Calculate conditional probabilities.
  • 4.6 * Calculate probabilities for independent events and for the union of two events.
  • 4.7 * Represent the probability distribution for a discrete random variable.
  • 4.8 * Calculate parameters for a discrete random variable.
  • 4.9 * Calculate parameters for linear combinations of random variables.
  • 4.10 * Estimate probabilities of binomial random variables using data from a simulation.
  • 4.11 * Calculate parameters for a binomial distribution.
  • 4.12 * Calculate probabilities for geometric random variables.

Unit 5: Sampling Distributions

  • 5.1 * Identify questions suggested by variation in statistics for samples collected from the same population.
  • 5.2 * Calculate the probability that a particular value lies in a given interval of a normal distribution.
  • 5.3 * Estimate sampling distributions using simulation .
  • 5.4 * Explain why an estimator is or is not unbiased.
  • 5.5 * Sampling Distributions for Sample Proportions § Classroom Resources >
  • 5.6 * Determineparametersof a sampling distribution foradifferenceinsample proportions.
  • 5.7 * Sampling Distributions for Sample Means UNLORC--31
  • 5.8 * Determineparametersofa sampling distribution for a differenceinsamplemeans.

Unit 6: Inference for Categorical Data — Proportions

  • 6.1 * Identify questions suggested by variation in the shapes of distributions of samples taken from the same population.
  • 6.2 * Identify an appropriate confidenceinterval procedure for a population proportion.
  • 6.3 * Interpretaconfidence interval for a population proportion.
  • 6.4 * to introduce inference tests) Exploring One-Variable Data UNIT
  • 6.5 * Interpreting p-Values VAR-6 The normal distribution may be used to model variation.
  • 6.6 * Concluding a Test for a Population Proportion DAT-3 Significancetestingallowsustomakedecisionsabouthypotheseswithina
  • 6.7 * Potential Errors When Performing Tests UNC-5 ProbabilitiesofTypeIandTypeIIerrorsinfluenceinference.
  • 6.8 * Confidence Intervals for the Difference of Two Proportions UNC-4
  • 6.9 * Justifying a Claim Based on a Confidence Interval for a Difference of
  • 6.10 * Setting Up a Test for the Difference of Two Population Proportion VAR-6
  • 6.11 * Carrying Out a Test for the Difference of Two Population Proportions VAR-6

Unit 7: Inference for Quantitative Data — Means

  • 7.1 * Introducing Statistics: Why Should I Worry About Error? VAR-1
  • 7.2 * Constructing a Confidence Interval for a Population Mean VAR-7
  • 7.3 * Justifying a Claim About a Population Mean Based on a Confidence Interval
  • 7.4 * Setting Up a Test for a Population Mean SKILLS Selecting Statistical
  • 7.5 * Calculate an appropriate test statistic for a population mean, including the mean differencebetweenvaluesin matched pairs.
  • 7.6 * .1 Consider a simple random sample from population1ofsize n ,mean μ ,andstandard deviationσ 1 and a sec1ond simple r 1andom samplefrompopulation2ofsize n2 ,mean μ2 , of populations 1 and 2 are normal or if both and standard deviation σ 2 . If the distributions n1 an
  • 7.7 * Interpretaconfidence intervalforadifferenceof population means.
  • 7.8 * Identify an appropriate selection of a testing methodforadifference of two population means.
  • 7.9 * Calculate an appropriate test statisticforadifferenceof two means.
  • 7.10 * Skills Focus: Selecting,

Unit 8: Inference for Categorical Data — Chi-Square

  • 8.1 * Identify questions suggested by variation between observed and expected counts in categorical data.
  • 8.2 * Describechi-square distributions.
  • 8.3 * Calculate the appropriate statisticforthechi-square testforgoodnessoffit.
  • 8.4 * Calculate expected counts fortwo-waytablesof categorical data.
  • 8.5 * Identify the null and alternative hypotheses forachi-squaretest for homogeneity or independence.
  • 8.6 * Carrying Out a Chi-Square Test for Homogeneity or Independence
  • 8.7 * Skills Focus: Selecting

Unit 9: Inference for Quantitative Data — Slopes

  • 9.1 * Identify questions suggested by variation in scatter plots.
  • 9.2 * C Identifyanappropriateconfidenceintervalprocedureforaslopeofaregression model.
  • 9.3 * G Interpretaconfidence interval for the slope of a regression model.
  • 9.4 * Identify the appropriate selection of a testing method for a slope of a regression model.
  • 9.5 * Calculate an appropriate test statistic for the slope of a regression model.
  • 9.6 * Skills Focus:

* Assessed on the AP Exam (per the Course and Exam Description). All topics listed; unmarked topics are course scope only.

AP® is a trademark registered by the College Board. Course and Exam Description content is used for educational reference; see College Board for the official CED.

AP Course and Exam Description (College Board)

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