Advanced Placement Statistics Course Outline 2010-2011
Exploring Data:
a) Constructing and interpreting graphical displays of distributions of univariate data (dotplot, stemplot, histogram, cumulative frequency plot)
i) Center and spread
ii) Clusters and gaps
iii) Outliers and other unusual features
iv) Shape
b) Summarizing distributions of univariate data
i) Measuring center: median, mean
ii) Measuring spread: range, interquartile range, standard deviation
iii) Measuring position: quartiles, percentiles, standardized scores (z-scores)
iv) Using boxplots
v) The effect of changing units on summary measures
c) Comparing distributions of univariate data (dotplots, back-to-back stemplots, parallel boxplots)
i) Comparing center and spread: within group, between group variation
ii) Comparing clusters and gaps
iii) Comparing outliers and other unusual features
iv) Comparing shapes
d) Exploring bivariate data
i) Analyzing patterns in scatterplots
ii) Correlation and linearity
iii) Least-squares regression line
iv) Residual plots, outliers, and influential points
v) Transformations to achieve linearity: logarithmic and power transformations
e) Exploring categorical data
i) Frequency tables and bar charts
ii) Marginal and joint frequencies for two-way tables
iii) Conditional relative frequencies and association
iv) Comparing distributions using bar charts
Sampling and Experimentation:
a) Overview of methods of data collection
i) Census
ii) Sample survey
iii) Experiment
iv) Observational study
b) Planning and conducting surveys
i) Characteristics of a well-designed and well-conducted survey
ii) Populations, samples, and random selection
iii) Sources of bias in sampling and surveys
iv) Sampling methods, including simple random sampling, stratified random sampling, and cluster sampling
c) Planning and conducting experiments
i) Characteristics of a well-designed and well-conducted experiment
ii) Treatments, control groups, experimental units, random assignments, and replication
iii) Sources of bias and confounding, including placebo effect and blinding
iv) Completely randomized design
v) Randomized block design, including matched pairs design
d) Generalizability of results and types of conclusions
a) Constructing and interpreting graphical displays of distributions of univariate data (dotplot, stemplot, histogram, cumulative frequency plot)
i) Center and spread
ii) Clusters and gaps
iii) Outliers and other unusual features
iv) Shape
b) Summarizing distributions of univariate data
i) Measuring center: median, mean
ii) Measuring spread: range, interquartile range, standard deviation
iii) Measuring position: quartiles, percentiles, standardized scores (z-scores)
iv) Using boxplots
v) The effect of changing units on summary measures
c) Comparing distributions of univariate data (dotplots, back-to-back stemplots, parallel boxplots)
i) Comparing center and spread: within group, between group variation
ii) Comparing clusters and gaps
iii) Comparing outliers and other unusual features
iv) Comparing shapes
d) Exploring bivariate data
i) Analyzing patterns in scatterplots
ii) Correlation and linearity
iii) Least-squares regression line
iv) Residual plots, outliers, and influential points
v) Transformations to achieve linearity: logarithmic and power transformations
e) Exploring categorical data
i) Frequency tables and bar charts
ii) Marginal and joint frequencies for two-way tables
iii) Conditional relative frequencies and association
iv) Comparing distributions using bar charts
Sampling and Experimentation:
a) Overview of methods of data collection
i) Census
ii) Sample survey
iii) Experiment
iv) Observational study
b) Planning and conducting surveys
i) Characteristics of a well-designed and well-conducted survey
ii) Populations, samples, and random selection
iii) Sources of bias in sampling and surveys
iv) Sampling methods, including simple random sampling, stratified random sampling, and cluster sampling
c) Planning and conducting experiments
i) Characteristics of a well-designed and well-conducted experiment
ii) Treatments, control groups, experimental units, random assignments, and replication
iii) Sources of bias and confounding, including placebo effect and blinding
iv) Completely randomized design
v) Randomized block design, including matched pairs design
d) Generalizability of results and types of conclusions