Download Course Syllabus

AP Statistics Syllabus
Fall 2014
Instructor: Mark Heinen
Location: Room 717
Phones 719.429.1539 (cell)
E-mails: [email protected] , [email protected]
Course Duration: Fall 2014 (86 each, 90 minute class periods)
Resource Materials:
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Primary text: Starnes, Tabor, Yates, and Moore. The Practice of Statistics. 5 th Edition, 2015
Secondary text: Triola, Mario F. Elementary Statistics. 10th Edition, 2006
Fathom 2 software from KCP Technologies, 2007
Microsoft Excel spreadsheet (various years)
Stat Disk Software from http://www.statdisk.org/
Meaning from Data, Professor Michael Starbird, video series
Texas Instrument tutorial videos on TI-84 and Nspire
Course Overview
AP Statistics will require you to apply most of the previous mathematics you have learned but
(more importantly) will demand critical thinking skills to be successful. While instruction will
typically be received individually, you should expect a number of projects that typically require
small group work. These small groups will permit you to develop your interpersonal skills and
expose you to the ideas and solutions proposed by others. You will honestly find that the ideas
of other are often superior to your own individual ideas. Specifically, other students in your
group will enhance your methodology and inferences skills.
Teaching materials for the course will come from textbooks, classroom lectures, periodicals,
videos, and the internet. Visit the high school website or see me for an exact course
description. This course requires use of technology. It is a given that you are technologically
proficient. (If not, I will make you so.) Visit my website regularly for updated assignment lists
and data files used in projects. Submit ALL projects in MS Word format (with any Excel
attachments) to my MSN e-mail address. Students are expected to secure the use of a TI-84 or
a TI-Nspire calculator. Other scientific / statistical calculators are permitted. Some TI-84
instruction will be taught in class but in general, proper use of your calculator is your
responsibility. See me for help after school. Typically, computers / laptops are permitted in
class and are required for projects and some assignments. Proficient use of MS Excel and
Fathom 2 is suggested. See me with questions about acquiring or using this software. Other
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AP Statistics Syllabus
Fall 2014
software such as Minitab is permitted. I will often use Mathcad for general computation and as
a container for assignments.
Projects / computer labs are also a major part of the course. Students complete three to four
major projects / labs each semester. A few smaller projects are not shown on the course outline
(below). Some of these projects are completed during class time, while others are completed
outside of class. Some of the projects will be small group work. These projects require students
to design surveys and experiments, gather data, analyze the data numerically and graphically,
and apply inferential statistics to draw conclusions for a population. These projects must be
submitted as professional word processed documents with all supporting calculations and
computer files attached or as appendices.
As the course progresses, the associated AP released questions will be reviewed. The unit
examinations will be patterned after the AP exam and will consist of multiple choice and free
response questions. Questions will be modeled after those found on the AP website or related
materials. Students are recommended to visit the AP stats website regularly to take advantage
of the site’s study materials.
Specific classroom rules / expectations / notebook requirements will be a separate handout at
the beginning of the course. Extensive review will be offeed prior to the Spring 2013 AP exam.
Statistics requires you to bridge the gap between mathematical knowledge and real world
application. Most importantly, statistics demands critically thinking through all parts of the
problem solving process especially your conclusion(s). As a high school student, this will be one
of the first courses where thinking is more important than doing. The days of just getting a
correct answer are gone. The reasoning and logic of your answers is more important.
Successfully completing this course will open your eyes to some of the stochastic truth and
fallacies of the world. It will more than adequately prepare you for success in post-secondary
education and make you one of the smartest dogs on the block.
Course Outline and Content
The course outline follows the four conceptual tools:
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Exploring Data: Describing patterns and departures from patterns
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Sampling and Experimentation: Planning and conducting a study
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Anticipating Patterns: Exploring random phenomena using probability and simulation
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Statistical Inference: Estimating population parameters and testing hypotheses
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AP Statistics Syllabus
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Week
The outline and content are shown by unit/topic by week by class below:
Major
Topic
(Unit)
Minor Topic
Intro
2
3
4
5
Unit 1 - Exploring Data (Describing patterns and departures from patterns)
1
Construction and
interpreting graphical
displays of univariate data
Summarizing distribution of
univariate data
Comparing distributions of
univariate data (dot plots, backto-back stem and leaf plots,
parallel box plots, frequency
diagrams)
Exploring bivariate data
Exploring categorical data
Content
"Is the die fair?" introductory example with exercises
Dot plots, Stem and Leaf Plots
Pareto and pie charts
Exploring the TI 84 / Nspire calculators. Preparing lists
and creating distributions
Frequency Distributions, Histograms
Relevance of center and spread, clusters and gaps,
shape, outliers, and unusual features
Creating and exploring frequency plots
Cumulative frequency plots creation and exploration
Measures of the center (mean, median, mode)
Measuring spread (range, interquartile range, standard
deviation) [Part 1]
Measuring spread (range, interquartile range, standard
deviation) [Part 2]
Measuring position and relative standings (quartiles,
percentiles, z-score introduction)
Study of box plots (more)
Comparing center and spread within and between
distributions (day 1)
Comparing center and spread within and between
distributions (day 2)
Comparing distribution shapes, clusters, gaps, outliers
and unusual features
Patterns in scatter plots
Correlation and linearity
Least squares regression line
Least squares regression line
Residual plots, outliers, and influential points
Regression Variation and prediction intervals
Transformations to achieve linearity ( logarithmic and
power transformations)
Excel Regression Computer Lab
Frequency tables and bar charts. Marginal and joint
frequency in 2-way tables
Conditional relative frequencies. Using bar charts to
compare distributions
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AP Statistics Syllabus
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Fall 2014
Unit Assessment
7
8
9
Unit 2 - Sampling and Experiment Design
Methods of Data Collection
Planning and conducting
surveys
Planning and conducting
experiments
Conclusions from
observation, surveys, and
experiments
10
11
12
Unit 3 - Anticipating Patterns (Exploring
random phenomena using probability and
simulation)
Unit Assessment
Probability
Combining independent
random variables
The Normal Distribution
Unit (Exploring Data) Review
Unit (Exploring Data) Test
Overview of methods of data collection: Census,
Survey, Experiment, Observational study
Characteristics of a well designed & conducted survey
Population, samples, and random selection
Sources of bias in sampling and surveys
Sampling methods: simple random sampling and
stratified random sampling
Treatments, control groups, experimental units,
random assignment, and replication
Sources of bias and confounding, placebo effect and
blinding
Completely randomized design
Randomized block design, including matched pairs
design
Multistage Sampling
In-class student analysis of different surveys /
experiments to generalize results and types of
conclusions.
Student presentation of survey and experiment
projects
Unit (Sampling and experiment design) Review
Unit (Sampling and experiment design) Test
Interpreting Probability (includes long run relative
frequencies)
Basic probability concepts and "Law of large numbers"
concept
Addition and multiplication rules
Conditional probability and independence, Counting
Basics: permutations and combinations
Simulation of random behavior and probability
distributions. Introduction to Excel use in simulation
Discrete random variables and the binomial and
Poisson distributions
Expected value (mean) and SD of a random variable
Independent vs. dependent variables
Mean and SD for sums and differences of independent
variables
Properties and tables of the Normal Distribution.
Introduction to the Standard Normal Distribution (Z)
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Sampling Distributions
13
14
15
16
17
Unit 4 - Statistical Inference (estimating population parameters and
testing hypothesis)
Unit Assessment
Estimating Population
Parameters (point
estimators & confident
intervals)
The normal distribution as a model for measurements.
Application of the Z distribution. Assessing normality.
Sampling distribution of sample proportion
Sampling distribution of sample mean
Central Limit Theorem development and implication
Sampling distribution of the difference between two
independent proportions / means
Simulation of sampling distributions
Student t distribution description and application
examples
Chi-square distribution description and applications
examples
Unit (Anticipating Patterns) Review
Unit (Anticipating Patterns) Test
Overview of estimating population parameters and
margin of errors. Logic of confidence intervals
Investigation of point estimators , unbiasedness, and
variability
Estimating a population proportion
Estimating a population mean (standard deviation
known)
Estimating a population mean (standard deviation NOT
known)
Confidence Interval for population variance and
sample size for calculating population mean and
variance
Confidence interval for a difference between 2
proportions
Confidence interval for the difference of two means
(paired and unpaired)
Mid-Unit Review (Estimating Population Parameters)
Mid-Unit Assessment
Tests of Significance
Mid-Unit Test (Estimating Population Parameters)
Overview of Hypotheses Testing. Logic of hypotheses
testing (part 1)
Logic of hypotheses testing (part 2)
Sample test for a proportion
Hypothesis test for a mean (sigma known)
Hypothesis test for a mean (sigma NOT known)
Testing a claim about standard deviation or variance.
Sample test for a difference between two proportions
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Hypothesis test for a difference between two means
(paired and unpaired)
Inferences from Matched Pairs
Chi-square test for goodness of fit, homogeneity of
proportions, and independence (1 and 2 way)
Test for the slope of a least-squares regression line
Confidence interval for the slope of a least-squares
regression line
18
Unit Assessment
Unit (statistical inference) Test
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