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Transcript
AP Statistics
1st Semester Final Exam Review
You should be able to….
 Look at a graph of a histogram, stemplot, or boxplot and determine if it is skewed to the right or left, has any
clusters or gaps, has any outliers, etc.
 Make a stemplot of a data set (with and without split stems).
 Determine the relative positions of the mean and median based on the shape of the graph.
 Estimate IQR given the cumulative proportions for values in a data set.
 Estimate the standard deviation of a mound-shaped graph.
 Know when it is appropriate to use the mean or the median as the best measure of center.
 Know which summary statistics are strongly affected by outliers.
 Conduct the outlier test from the 5-number summary.
 Identify the five-number summary and range of a boxplot.
 Draw & interpret segmented bar graphs.
 Know the properties of the normal distribution.
 Find “standardized scores.”
 Find normal probabilities using z-scores and the standard normal table.
 Find the regression line of a data set using both STAT-CALC-8 and the formulas for slope and y-intercept.
 Interpret the slope, y-intercept and coefficient of determination of a regression line in context.
 Describe and analyze points on a scatterplot.
 Estimate the correlation coefficient given a scatterplot.
 Know the properties of correlation coefficient.
 Identify what the residual plot looks like given a scatterplot.
 Identify outliers and influential points on a scatterplot & discuss their properties.
 Linearize data using (x, logy) and (logx, logy). Then find the line of best fit for the transformed data set.
 Know which transformation works best for an exponential model / power model.
 Know when causation can be determined and when it cannot.
 Describe the difference between an experiment and an observational study.
 Discuss the four main ways to collect data: census, sampling, experiment, simulation.
 Describe the six sampling methods (names, characteristics, examples, which are random, which are biased).
 Identify the three types of bias: undercoverage, nonresponse, response.
 Identify the three experimental designs and the three principles of experimentation.
 Identify explanatory & response variables in an experiment, plus the experimental groups and the control group.
 Find a conditional probability from a table.
 Interpret the Law of Large Numbers.
 Interpret the probability distribution of a discrete random variable & find a missing probability in it.
 Know that the joint probability of two independent events , P(A and B) = P(A)P(B).
 Find expected value given a game scenario.
 Determine what happens to the mean and standard deviation of a random variable as a result of a linear
transformation.
 Combine means and standard deviations for two independent variables.
 Solve a golf problem like we just did in class!
Know these terms…
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Symmetric
Cluster (on a graph, not sample)
Interquartile range
First quartile
Third quartile
Variance
Mean
Standard deviation
Outlier
Cumulative proportion
Five number summary
Correlation coefficient
Influential point
Census
sampling
Experiment
observational study
Simple random sample
Voluntary response sample
Stratified random sample
Homogeneous
Undercoverage
Nonresponse
Response bias
Control
Randomization
Replication
Completely randomized design
Block design
Matched pairs design
Explanatory variable
Response variable
Control group
Experimental group
Standardized score
Standard normal curve
Expected value
Joint probability = P(A and B)