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Categorical and Quantitative VariablesS-ID.A
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Dot Plots, Histograms and Box PlotsS-ID.A.1
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Center: Mean and MedianS-ID.A.2
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Spread: Range, Interquartile Range and Standard DeviationS-ID.A.2
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Shape, Outliers and Effects on Summary StatisticsS-ID.A.3
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Reading and Comparing Stem-and-Leaf PlotsS-ID.A.1
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Choosing the Right Graph for a Data SetS-ID.A.1
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Comparing Two Distributions by Center, Spread and ShapeS-ID.A.3
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Finding Outliers with the 1.5 IQR RuleS-ID.A.3
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Five-Number Summary and QuartilesS-ID.A.2
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The Normal Curve and the Empirical RuleS-ID.A.4
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Z-ScoresS-ID.A.4
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Finding Proportions Under a Normal CurveS-ID.A.4
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Deciding When a Normal Model FitsS-ID.A
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Finding a Value from a Percentile on a Normal CurveS-ID.A.4
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Comparing Values from Different Distributions with Z-ScoresS-ID.A.4
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Effect of Adding or Multiplying Every Data ValueS-ID.A.2
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01
Two-Way Tables and Relative FrequenciesS-ID.B.5
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Scatter Plots and AssociationS-ID.B.6
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Fitting and Using Linear ModelsS-ID.B.6.a
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Residuals and Residual PlotsS-ID.B.6.b
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Correlation Coefficient and Interpreting SlopeS-ID.C
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Correlation Versus CausationS-ID.C.9
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Interpreting Marginal and Conditional Relative FrequenciesS-ID.B.5
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Interpreting the Y-Intercept of a Linear Model in ContextS-ID.C.7
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Influential Points and ExtrapolationS-ID.B.6
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Using Exponential or Quadratic Models for Data That CurveS-ID.B.6.a
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Spotting Lurking Variables and ConfoundingS-ID.C.9
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01
Population, Sample and ParameterS-IC.A.1
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Random Sampling MethodsS-IC.B.3
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Sources of Bias in SurveysS-IC.B.3
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Observational Studies Versus ExperimentsS-IC.B.3
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Designing Experiments with Random AssignmentS-IC.B.3
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Stratified, Cluster and Systematic Samples ComparedS-IC.B.3
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Blocking, Control Groups and Placebos in ExperimentsS-IC.B.3
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01
Sample Spaces and EventsS-CP.A.1
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Probability Rules: Union, Intersection, ComplementS-CP.B.7
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Conditional ProbabilityS-CP.A.3
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Independent EventsS-CP.A.2
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Counting: Permutations and Combinations (+)S-CP.B.9
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Probability with Tree DiagramsS-CP.A.3
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Checking Independence with Two-Way TablesS-CP.A.4
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The Multiplication Rule for Dependent EventsS-CP.B.8
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Using Conditional Probability in Everyday DecisionsS-CP.A.5
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01
Probability Distributions and Expected ValueS-MD.A
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Expected Value in Decisions and Games of ChanceS-MD.B
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Binomial Probability ModelsS-MD
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Simulation to Model Random EventsS-IC.A.2
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Mean and Standard Deviation of a Random VariableS-MD.A.2
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Mean and Standard Deviation of a Binomial DistributionS-MD
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Law of Large Numbers and Long-Run Relative FrequencyS-MD.A
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01
Sampling VariabilityS-IC.A
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Sampling Distribution of a ProportionS-IC.B
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Margin of ErrorS-IC.B.4
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Confidence Intervals for a ProportionS-IC.B.4
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Sampling Distribution of a Sample MeanS-IC.B
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Interpreting a Confidence Level CorrectlyS-IC.B.4
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How Sample Size Affects Margin of ErrorS-IC.B.4
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01
Using Simulation to Test a ClaimS-IC.A.2
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Hypothesis Testing Ideas: Claims and EvidenceS-IC.B
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Comparing Two Groups with RandomizationS-IC.B.5
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Significance and Errors in DecisionsS-IC.B
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Evaluating Reports Based on DataS-IC.B.6
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Interpreting a P-Value in ContextS-IC.B
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Comparing Two Proportions with a Randomization TestS-IC.B.5
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