Microsoft word - ap statstics _365_ audit version curriculum map.doc

In the twenty-first century, computers will do a lot of the work that people used to do. Even in today’s workplace, there is little need for someone to add up daily invoices or compute sales tax. Engineers and scientists already use computer programs to do calculations and solve equations.
Some important skills for the twenty-first century will be the ability to think creatively about mathematics and to reason
logically. It will also be important to work as a team member and to be able to explain your thinking. In keeping up with our schools mission statement, I will do my best to prepare you for college and with your cooperation and your parents help to prepare you to be a valuable citizen for the rest of your life.
This course will help you to develop many of the skills you will need for the future. On the way, you will see the value of
creative thinking, but the key question will always be:”What do YOU think?” Prerequisites: 88 average in Honors Algebra II and teacher recommendation. This is a rigorous course based on on the syllabus defined by the Advanced Placement Committee. Major themes encompass exploring data; patterns and departure from patterns; anticipating patterns; producing models using probability and simulation; planning a study; deciding what and how to measure; and statistical inference; confirming models. Graphing calculators required to be obtained by the student, and access to a computer is needed, school will provide access in school only. Calculator: In this class calculator use is essential as we use TI-Navigator almost daily.
You should have basic knowledge of using TI-84 or TI-83 + . You should understand how to input data into lists and
Course Goals: The goals of this course follow the standards outlined for Advanced Placement Statistics. They are numbered and will be inserted into the pacing guide to indicate when various lessons target an individual goal. Computer: We use the computer in conjunction with the TI-Navigator as well as with a program called MINITAB. G1: Exploring Data: Observing patterns and departure from patterns G2: Planning a study: Deciding what and how to measure G3:Anticipating Patterns: Producing models using probability theory and simulation

G4: Statistical Inference: Confirming Data TEXT: Introduction to the practice of STATISTICS (SECOND EDITION)

Course materials: Calculator (TI 83 plus or TI 84), pencil, notebook, straight edge. GRADING: HOMEWORK------------------10% CLASS-PARTICIPATION---10% QUIZZES-----------------------30% TESTS---------------------------50% MID-TERM GRADE: is the average of quarter grades and mid-term exam grade. FINAL GRADE is the average of all the quarter grades, mid-term exam grade and final exam grade. NOTA-BENE: Mid-term and final exams are going to be cumulative. PROJECT: ONE OR MORE PER TERM WORTH ONE TEST GRADE Project 1: Are estimates influenced by “anchoring” numbers?

You will be graded on: How well you design the experiment, displaying your data in an appropriate graph and then describing and analyzing it using the vocabulary of the chapter 2, center, variation, distribution, outliers and how the data is affected by changing characteristics of the data over time. Project 2. Capture recapture.

Using a large bag of M@M (not counted), you will try to estimate the number of M@M by experimenting with the method of capture recapture. Justify the report by making reference to probability and counting techniques as taught in this chapter. Project 3. Construct confidence interval, collecting data by choosing a simple random sample to estimate the population mean.

Justify each step of the experiment with appropriate statistical terminology. Project 4. This project will be done by a group of 3-4 students.

Each group will design an experiment and perform an appropriate statistical test to answer the following questions.

You will ask these two questions. a) Which political party do you favor most? b) If you were to make up an absence excuse of a flat tire, which tire would you name? Answer the following questions.

1) Political party choice is independent of the gender of the subject. 2) The tire identified as being flat is independent of the gender of the subject. 3) Political party choice is independent of the tire identified as being flat. Three final projects: Using the student body of the High School will design three experiments: 1) Test the validity that the mean grade in the high school is 68.5 2) The difference in the height of boys and girls is more than 3 inches. 3) Test the validity that the mean grade in the high school for mathematics 59.9. All three projects are to be done in accordance with the rules of statistics learned in this class, and to be presented typed and in the format provided below.

1) Parameter of Interest 2) Choice of Test ________________________________________________________________________ 3) Check of Assumptions
4) Null Hypothesis: Ho: (in words) ___________________________________________ ______________________________________________________
Ho: (in symbols) _________________________________________
5) Alternative Hypothesis: Ha: (in words) _______________________________________________________________________
______________________________________________________
Ha: (in symbols) _________________________________________
6) Probability Statement: P-value = probability (_________________________________ _______________________________________________________________________
8) Test: Level of Significance α = _______ Sketch of Sampling Distribution assuming Ho is true: 9) P-value Reconciliation of Critical Value with Rejection Region: Exact p-value: 10) Recommended Decisions Regarding Ho: Regarding significance: 11) Interpretation (in the context of the problem)

Chapter 1 Looking at Data: Distributions 1.1 DisplayingDistributions Exploratory analysis of data makes use of graphical and numerical techniques to study patterns and departures from patterns. Emphasis should be placed graphical and numerical displays and 1.2 DescribingDistributions 1.3 The Normal Distributions Exploratory analysis of data makes use of graphical and numerical techniques to study patterns and departures from patterns. Emphasis should be placed graphical and numerical displays and Chapter 2 Looking at Data: Relationships 2.1 Scatterplots Data must be collected according to a information on a conjecture is to be obtained. This plan includes clarifying method of data collection and analysis. 2.2 Least Squares Regression 2.3 An Application: Exponential Growth 2.4 Correlation collected according to a well-developed conjecture is to be obtained. This plan includes clarifying the question and 2.5 Relations in Categorical 2.6 The Questions of Causation Chapter 3 Producing Data collected according to a well-developed conjecture is to be obtained. This plan 3.2 Design of Experiments includes clarifying the question and 3.3 Sampling Design collected according to a well-developed conjecture is to be obtained. This plan
Week 3.4 Toward Statistical Inference Calculator, TI – includes clarifying the question and Chapter 4 Probability: The Study of Randomness 4.1 Probability Models anticipating what the distribution of data should look like under a given 4.2 Random Variables 4.3 Means and Variances of Random Variables anticipating what the distribution of data should look like under a given 4.4 Probability Laws Chapter 5 From Probability to Inference 5.1 Counts and Proportions 5.2 Sample Means 5.3 Control Charts Chapter 6 Introduction to Inference 6.1 Estimating with Confidence Introduction to the 6.2 Test of Significance 6.3 Use and Abuse of Tests Chapter 7 Inference for Distributions 7.1 Inference for the Mean of a Population 7.2 Comparing Two Means 7.3 Inference for Population
Robustness of Normal Inference David S. Moore
Chapter 8 Inference for Count Data 8.1 Inference for a Single Proportion 8.2 Comparing Two Proportions 8.3 Inference for Two-Way
and diagnostic methods. Inference from data can be thought of as the process of selecting a reasonable model, including a statement in probability language, of how confident one can be about the selection.
Chapter 9 Inference for Regressions 9.1 Simple Linear Regressions 9.2 Multiple Linear Regression
and diagnostic methods. Inference from data can be thought of as the process of selecting a reasonable model, including a statement in probability language, of how confident one can be about the selection.
Chapter 10 Analysis of Variance 10.1 One-Way Analysis of Variance 10.2 Two-Way Analysis of Variance
Main Effects and Interactions ANOVA Table for Two-Way

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