2 Possibly Qualified 1 No Recommendation I. Exploring Data Describing patterns and departures from
patterns (20%-30%) Exploring analysis of data makes use of graphical and numerical techniques to study patterns and departures from patterns. Emphasis should be placed on interpreting information from graphical and numerical displays and summaries. I. Exploring Data A.
Constructing and interpreting graphical displays of distributions of univariate data (dotplot, stemplot, histogram, cumulative frequency plot) Center and spread 2. Clusters and gaps 3. Outliers and other unusual features 4. Shape 1.
I. Exploring Data B. Summarizing distributions of univariate data Measuring center: median, mean Measuring spread: range, interquartile range, standard deviation 3. Measuring position: quartiles, percentiles,
standardized scores (z-scores) 4. Using boxplots 5. The effect of changing units on summary measures 1. 2. I. Exploring Data C.
Comparing distributions of univariate data (dotplots, back-to-back stemplots, parallel boxplots) Comparing center and spread: within group, between group variables 2. Comparing clusters and gaps 3. Comparing outliers and other unusual features 4. Comparing shapes 1.
MC Example MC Example MC Example 2006 FR#1 The Catapults Two parents have each built a toy catapult for use in a game at an elementary school fair. To play the game, the
students will attempt to launch Ping-Pong balls from the catapults so that the balls land within a 5-centimeter band. A target line will be drawn through the middle of the band, as shown in the figure below. All points on the target line are equidistant from the launching location. If a ball lands within the shaded band, the student will win a prize. 2006 FR#1 The Catapults The parents have constructed the two catapults according to slightly different plans. They want to test these
catapults before building additional ones. Under identical conditions, the parents launch 40 Ping-Pong balls from each catapult and measure the distance that the ball travels before landing. Distances to the nearest centimeter are graphed in the dotplot below. 2006 FR#1 The Catapults Comment on any similarities and any differences in the two distributions of distances traveled by balls launched from catapult A and
catapult B. b) If the parents want to maximize the probability of having the Ping-Pong balls land within the band, which one of the catapults, A or B, would be better to use than the other? Justify your choice. c) Using the catapult that you chose in part (b), how many centimeters from the target line should this catapult be placed? Explain why you chose this distance.
a) I. Exploring Data D. Exploring bivariate data 1. 2. 3. 4.
5. Analyzing patterns in scatterplots Correlation and linearity Least-squares regression line Residuals plots, outliers, and influential points Transformations to achieve linearity: logarithmic and power transformations
MC Example MC Example MC Example Correlation r Strength of linear association I. Exploring Data
E. Exploring categorical data Frequency tables and bar charts 2. Marginal and joint frequencies for two-way tables 3. Conditional relative frequencies and association 4. Comparing distributions using bar charts 1.
FR Example This is an example of a Free Response question in which the first parts involve Exploratory Data Analysis and later parts involve inference. II. Sampling and Experimentation Planning and conducting a study (10%-15%)
Data must be collected according to a welldeveloped plan if valid information on a conjecture is to be obtained. This includes clarifying the question and deciding upon a method of data collection and analysis. II. Sampling and Experimentation A. Overview of methods of data collection
Census 2. Sample survey 3. Experiment 4. Observational study 1. II. Sampling and Experimentation B.
Planning and conducting surveys Characteristics of a well-designed and well-conducted survey 2. Populations, samples, and random selection 3. Sources of bias in sampling and surveys 4. Sampling methods, including simple random sampling, stratified random sampling, and cluster sampling 1.
MC Example MC Example MC Example II. Sampling and Experimentation C.
Planning and conducting experiments Characteristics of a well-designed and well-conducted experiment 2. Treatments, control groups, experimental units, random assignments, and replication 3. Sources of bias and confounding, including placebo effect and blinding 4. Randomized block design, including
matched pairs design 1. MC Example MC Example MC Example MC Example
Anticipating Patterns A. Probability 1. 2. 3. 4. 5.
6. Interpreting probability, including long-run relative frequency interpretation Law of Large Numbers concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including binomial and geometric
Simulation of random behavior and probability distributions Mean (expected value) and standard deviation of a random variable and linear transformation of a random variable MC Example MC Example
MC Example Probability Sample Multiple Choice All bags entering a research facility are screened. Ninety-seven percent of the bags that contain forbidden material trigger an alarm. Fifteen percent of the bags that do not contain forbidden material also trigger the alarm. If 1 out of every 1,000
bags entering the building contains forbidden material, what is the probability that a bag that triggers the alarm will actually contain forbidden material? Organize the Problem Label the Events F Bag Contains Forbidden Material A Bag Triggers an Alarm
Determine the Given Probabilities P(A|F) = 0.97 P(A|FC) = 0.15 P(F) = 0.001 Determine the Question P(F|A) ? Set up a Tree Diagram A
0.97 F 0.03 0.001 AC Non-Conditional Probabilities A
0.999 0.15 FC 0.85 AC
Conditional Probabilities Calculate the Probability P(F|A) = P(F and A) / P(A) P(A) = P(F and A) or P(FC and A) = .001(.97) + .999(.15)
= .15082 P(F and A) = .001(.97) = .00097 P(F|A) = .00097/.15082 = 0.006 III. Anticipating Patterns B. Combining independent random variables
Notion of independence versus dependence 2. Mean and standard deviation for sums and differences of independent random variables 1. MC Example MC Example
MC Example MC Example 2002 AP STATISTICS FR#3 - The Runners There are 4 runners on the New High School team. The team is planning to participate in a
race in which each runner runs a mile. The team time is the sum of the individual times for the 4 runners. Assume that the individual times of the 4 runners are all independent of each other. The individual times, in minutes, of the runners in similar races are approximately normally distributed with the following means and standard deviations. (a) Runner 3 thinks that he can run a mile in less than 4.2 minutes in the next race. Is this
likely to happen? Explain. (b) The distribution of possible team times is approximately normal. What are the mean and standard deviation of this distribution? (c) Suppose the teams best time to date is 18.4 minutes. What is the probability that the team will beat its own best time in the next race? Runne r
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