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要求|美国高中学分课 36周 AP Statistics( 二 )


Essential Question: Does data always reveal the truth?
Objectives:
Identify and interpret the measures of center: mean, median and mode
Identify quartiles and the five-number summary
Identify and interpret the measures of spread: range, IQR and standard deviation
Determine if any outliers exist in a data set
Construct and interpret boxplots
Interpret numerical summaries to compare quantitative data distributions
Week 5: Modeling with the Normal Distribution
Essential Question: What is normal?
Objectives:
Identify and interpret measures of position: percentiles and z-scores
Identify the effect of adding, subtracting, multiplying or dividing by a constant on the shape, center and spread of a data distribution
Identify the normal distribution and its characteristics
Use the 68-95-99.7 Rule to estimate the proportion of observations of a normal distribution
Use the standard normal distribution to determine the proportion of values in a particular interval
Use technology to interpret normal distributions
Week 6: Scatterplots and Correlation
Essential Question: How can we determine if there is a relationship between two quantitative variables?
Objectives:
Identify and interpret scatterplots
Identify and interpret the strength and direction of a scatterplot
Determine the difference between association and correlation
Interpret the correlation coefficient of bivariate data
Week 7: Linear Regression
Essential Question: How can we model the linear relationship between two quantitative variables?
Objectives:
Identify if a scatterplot takes on a linear form
Identify and interpret the least-squares regression line
Find and describe residuals
Construct and interpret residual plots
Identify and interpret the coefficient of determination
Explain why association does not imply causation
Interpret the effect of unusual features and outliers
Week 8: Transforming Data to Achieve Linearity
Essential Question: How can we achieve linear data?
Objectives:
Transform data with powers
Transform data with roots
Transform data with logarithms
Week 9: Sampling Methods
Essential Question: How can we gather data?
Objectives:
Identify the difference between a population and a sample
Distinguish between good and bad sampling methods
Identify advantages and disadvantages of various sampling methods
Apply a table of random digits
Identify possible bias in sampling methods
Week 10: Experimental Design
Essential Question: How can we gather data?
Objectives:
Identify the difference between an observational study and an experiment
Identify a lurking variable and their affect on data
Explain the importance of random assignment
Identify the effect of a placebo
Identify experimental design
Week 11: Probability and Simulation
Essential Question: Is what should happen what will happen?
Objectives:
Interpret the meaning of probability
Relate probability to a relative frequency
Use simulation to model chance behavior
Week 12: Probability Rules
Essential Question: Is what should happen what will happen?
Objectives:
Describe the probability distribution of an experiment
Identify and apply the basic probability rules: complement rule, and addition rule for mutually exclusive events
Apply Venn diagrams to model an experiment involving two events
Identify and apply the general addition rule
Week 13: Independence and Conditional Probabilities
Essential Question: Is what should happen what will happen?
Objectives:
Identify and apply tree diagrams to determine the chance of compound events
Identify and apply the multiplication rule
Identify events as independent or dependent


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