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Pre-AP Statistics

 

Course Overview

 

What is this course? Pre-AP Statistics is a course designed to provide students with the skills and foundational knowledge needed to succeed in the college-level AP Statistics course and exam. It teaches students how to collect, analyze, and interpret data, fostering important mathematical reasoning skills like creating models and engaging in arguments.  

 

Who should take this course? Pre-AP Statistics is a great choice for students who enjoy working with data, recognizing patterns, and making logical arguments based on evidence. If you like math but prefer real-world applications over abstract concepts, this course is for you!

 

This class is an especially useful stepping stone for students planning to take AP Statistics with a view to pursuing careers or college majors in business, psychology, biology, economics, social sciences, political science, and data science. 




Course Skills

 

The following four skills will be cycled throughout all units we will learn in:

 

  • Select methods for collecting and/or analyzing data for statistical inference

  • Describe patterns, trends, associations, and relationships in data

  • Explore random phenomena

  • Develop an explanation or justify a conclusion using evidence from data, definitions, or statistical inference




Materials

 

  • Charged Chromebook

  • Writing Utensil 

  • Three Ring Binder or Folder 

  • Graphing Calculator – TI-84 or TI-84 Plus is recommended. We have a classroom set if you are unable to obtain your own or are not planning on requiring it past high school.

  • Textbook – The Practice of Statisticsis available in class.



Grading/Reassessment

 

  • Tests/Quizzes – AP Style Multiple Choice and Free Response Problems

  • Unit Projects – End of unit projects

  • Daily Work – Homework, lesson activities, etc.

 

MP 1 and 3: 10% CW/HW                     MP 2 and 4: 10% CW/HW

                     30% Quizzes/Projects                           20% Quizzes/Projects

                     60% Tests                                             50% Tests

                                                                                   20% Exams



Reassessments are available upon request. In order to reassess you must first make sure that you have gone through the assessment and made corrections/restudied. Have you done the following:

 

  • Identify what your mistakes are and explain – This can include understanding of the question, operational errors, use of the wrong method, or something else. “I didn’t know how to answer the question” is not an acceptable answer. Your gaps/errors must be explained.

  • Indicate how to solve the problem – Explain in a few words the process you will use to solve the problem. 

  • Work out the test problem(s) showing detail and arriving at a correct solution.

 

You are welcome to get extra help with this process if needed. However, you cannot get help from the teacher on the same day you reassess. 

 

  • You can retake Any test or quiz.

  • You must retake the Entire test within 10 school days.

  • Second Grade Stands

  • No retake option for scores below 30% of class average.

 

Late work: Students absent from school have the same number of days to make up assignments. Otherwise, assignments turned in a day or two late will receive 75%. Any work not turned in after 3 days will not be accepted. Any assignments that were due on the date(s) of your absence are due immediately upon your return to class.




AI Policy

 

You are welcome to use generative AI tools as a resource for learning, such as brainstorming ideas, checking your understanding, or getting help with explanations. However, AI should not complete problems or assignments for you. All work you submit must be your own, demonstrating your understanding and effort. Misuse of AI—such as copying responses without critical thinking—will be considered academic dishonesty. If you use AI in an appropriate way, be prepared to explain how it helped you and what you learned from it.



Course Sequencing*.

 

Unit 1: Exploring One Variable Data: VAR, UNC

 

Material Covered

CED Topics

CED Skills

Notes 1 – Categorical Data: Tables and Bar Graphs

  • VAR-1.A Identify questions to be answered, based on variation in one-variable data.

  • VAR-1.B Identify variables in a set of data.

  • VAR-1.C Classify types of variables.

  • UNC-1.A Represent categorical data using frequency or relative frequency tables.

  • UNC-1.B Describe categorical data represented in frequency or relative tables.

  • UNC-1.C Represent categorical data graphically.

  • UNC-1.D Describe categorical data represented graphically.

  • UNC-1.E Compare multiple sets of categorical data.

  • UNC-1.F Classify types of quantitative variables.

1.1, 1.2, 1.3, 1.4

1.A, 2.A, 2.B, 2.D

Notes 2 – Histograms and Ogives

  • UNC-1.G Represent quantitative data graphically.

1.5, 1.6

2.A, 2.B

Notes 3 – Stemplots and Dotplots

  • UNC-1.G Represent quantitative data graphically.

1.5, 1.6

2.A, 2.B

Notes 4 – Measures of Center and Spread

  • UNC-1.H Describe the characteristics of quantitative data distributions.

  • UNC-1.I Calculate measures of center and position for quantitative data.

  • UNC-1.J Calculate measures of variability for quantitative data.

  • UNC-1.K Explain the selection of a particular measure of center and/or variability for describing a set of quantitative data.

1.7, 1.8

2.A, 2.B, 2.C, 4.B

Notes 5 – Boxplots and Outliers

  • UNC-1.L Represent summary statistics for quantitative data graphically.

  • UNC-1.M Describe summary statistics of quantitative data represented graphically.

1.7, 1.8

2.A, 2.B, 2.C, 4.B

Notes 6 – One Variable Statistics with the TI-84

  • In this lesson, students will learn how to input data into a list on the TI-84 calculator, create and adjust histograms and boxplots, and calculate one-variable summary statistics

1.5, 1.7, 1.8

2.A, 2.B, 2.C, 4.B

Notes 7 – Comparing Distributions

  • UNC-1.N Compare graphical representations for multiple sets of quantitative data.

  • UNC-1.O Compare summary statistics for multiple sets of quantitative data.

1.9

2.D

Notes 8 – The Normal Curve

  • VAR-2.A Compare a data distribution to the normal distribution model.

1.10

2.D, 3.A

Notes 9 – The Standard Normal Curve

  • VAR-2.C Compare measures of relative position in data sets

1.10

2.D, 3.A

Notes 10 – Connecting Raw Data, Z-Scores, and Percentages

  • VAR-2.B Determine proportions and percentiles from a normal distribution.

1.10

2.D, 3.A

 

Unit Assessments*:

  • Unit 1 Quiz: 10 multiple choice questions and 1 free response question

  • Unit 1 Test: 15 multiple choice questions and 1 free response question

Unit Project: Misleading Graphs Activity*

  • Students find data to represent visually, both correctly and incorrectly.

  • CED Skills: 2.A, 2.B, 2.D




Unit 2: Exploring Two Variable Data: VAR, UNC, DAT

 

Material Covered

CED Topics

CED Skills

Notes 1 – Two Categorical Variables 

  • UNC-1.P Compare numerical and graphical representations for two categorical variables.

  • UNC-1.Q Calculate statistics for two categorical variables.

  • UNC-1.R Compare statistics for two categorical variables.

2.1, 2.2, 2.3

1.A, 2.C, 2.D

Notes 2 – Scatterplots and Correlation

  • VAR-1.D Identify questions to be answered about possible relationships in data.

  • UNC-1.S Represent bivariate quantitative data using scatterplots.

  • DAT-1.A Describe the characteristics of a scatter plot.

  • DAT-1.B Determine the correlation for a linear relationship.

  • DAT-1.C Interpret the correlation for a linear relationship.

2.4, 2.5

2.A, 2.B, 2.C, 4.B

Notes 3 – Linear Regression

  • DAT-1.D Calculate a predicted response value using a linear regression model.

  • DAT-1.G Estimate parameters for the least-squares regression line model.

  • DAT-1.H Interpret coefficients for the least-squares regression line model.

2.6, 2.8

2.C, 4.B

Notes 4 – Residuals

  • DAT-1.E Represent differences between measured and predicted responses using residual plots.

  • DAT-1.F Describe the form of association of bivariate data using residual plots.

2.7

2.A, 2.B

Notes 4 – Influential Points and Departure from Linearity

  • DAT-1.I Identify influential points in regression.

  • DAT-1.J Calculate a predicted response using a least-squares regression line for a transformed data set.

2.9

2.A, 2.C

 

Unit Assessments*:

  • Unit 2 Quiz: 10 multiple choice questions and 1 free response question

  • Unit 2 Test: 15 multiple choice questions and 1 free response question

Unit Project: Addition vs Multiplication Facts*

  • Students will gather data in class on their ability to complete a set of basic addition facts and a set of basic multiplication facts and complete a linear regression analysis on the resulting relationship.

  • CED Skills: 2.A, 2.B, 2.C, 4.B




Unit 3: Collecting Data: VAR, UNC

 

Material Covered

CED Topics

CED Skills

Notes 1 – Types of Studies

  • VAR-1.E Identify questions to be answered about data collection methods.

  • DAT-2.A Identify the type of a study.

  • DAT-2.B Identify appropriate generalizations and determinations based on observational studies.

  • VAR-3.A Identify the components of an experiment.

3.1, 3.2

1.A, 1.C, 4.A

Notes 2 – Sampling Methods

  • DAT-2.C Identify a sampling method, given a description of a study.

3.3

1.C

Notes 3 – Bias in Studies

  • DAT-2.D Explain why a particular sampling method is or is not appropriate for a given situation.

  • DAT-2.E Identify potential sources of bias in sampling methods.

3.4

1.C

Notes 4 – Experimental Design

  • VAR-3.B Describe elements of a well-designed experiment

  • VAR-3.C Compare experimental designs and methods.

  • VAR-3.D Explain why a particular experimental design is appropriate.

3.5, 3.6

1.B, 1.C

Notes 5 – Scope of Inference

  • VAR-3.D Explain why a particular experimental design is appropriate.

  • VAR-3.E Interpret the results of a well-designed experiment.

3.7

4.B

 

Unit Assessments*:

  • Unit 3 Quiz: 10 multiple choice questions and 1 free response question

  • Unit 3 Test: 15 multiple choice questions and 1 free response question

Unit Project: Sample Survey Project*

  • Students will design a survey to test a bias of their choosing. They will describe how they randomly select people to complete their survey and will then report their results in a visual aid.

  • CED Skills: 4.A, 4.B, 1.B, 1.C




Unit 4: Probability, Random Variables, and Probability Distributions: VAR, UNC

 

Material Covered

CED Topics

CED Skills

Notes 1 – Basic Probability and Simulations

  • VAR-1.F Identify questions suggested by patterns in data.

  • UNC-2.A Estimate probabilities using simulation

  • VAR-4.A Calculate probabilities for events and their complements.

  • VAR-4.B Interpret probabilities for events.

4.1, 4.2, 4.3

1.A, 3.A, 4.B

Notes 2 – The Addition Rule

  • VAR-4.A Calculate probabilities for events and their complements.

  • VAR-4.B Interpret probabilities for events.

  • VAR-4.C Explain why two events are (or are not) mutually exclusive.

4.4

4.B

Notes 3 – Venn Diagrams, Unions, and Intersections

  • VAR-4.E Calculate probabilities for independent events and for the union of two events.

4.3, 4.4, 4.6

3.A, 4.B

Notes 4 – The Multiplication Rule and Conditional Probability

  • VAR-4.D Calculate conditional probabilities

4.5, 4.6

3.A

Notes 5 – Discrete and Continuous Random Variables

  • VAR-5.A Represent the probability distribution for a discrete random variable

  • VAR-5.B Interpret a probability distribution.

  • VAR-5.C Calculate parameters for a discrete random variable.

  • VAR-5.D Interpret parameters for a discrete random variable.

4.7, 4.8

2.B, 3.B, 4.B

Notes 6 – Combining Random Variables

  • VAR-5.E Calculate parameters for linear combinations of random variables

  • VAR-5.F Describe the effects of linear transformations of parameters of random variables

4.9

3.B, 3.C

Notes 7 – The Binomial Distribution

  • UNC-3.A Estimate probabilities of binomial random variables using data from a simulation.

  • UNC-3.B Calculate probabilities for a binomial distribution.

  • UNC-3.C Calculate parameters for a binomial distribution.

  • UNC-3.D Interpret probabilities and parameters for a binomial distribution

4.10, 4.11

3.A, 3.B, 4.B

Notes 8 – The Geometric Distribution

  • UNC-3.E Calculate probabilities for geometric random variables.

  • UNC-3.F Calculate parameters of a geometric distribution.

  • UNC-3.G Interpret probabilities and parameters for a geometric distribution.

4.12

3.A, 3.B, 4.B

 

Unit Assessments*:

  • Unit 4 Quiz: 10 multiple choice questions and 1 free response question

  • Unit 4 Test: 15 multiple choice questions and 1 free response question

Unit Project: Make Your Own Casino*

  • Students create 3 games of chance to practice developing a probability distribution: one where the player wins, the house wins, and one where the game breaks even.

  • CED Skills: 3.A, 4.B




Unit 5: Sampling Distributions: VAR, UNC

 

Material Covered

CED Topics

CED Skills

Notes 1 – The Normal Distribution and Combining Normal Random Variables

  • VAR-6.A: Calculate the probability that a particular value lies in a given interval of a normal distribution.

  • VAR-6.B Determine the interval associated with a given area in a normal distribution.

  • VAR-6.C Determine the appropriateness of using the normal distribution to approximate probabilities for unknown distributions

  • VAR-5.E Calculate parameters for linear combinations of random variables

5.2

3.A, 3.C

Notes 2 – Sampling Distribution of a Sample Proportion

  • UNC-3.I Explain why an estimator is or is not unbiased.

  • UNC-3.J Calculate estimates for a population parameter.

  • UNC-3.K Determine parameters of a sampling distribution for sample proportions.

  • UNC-3.L Determine whether a sampling distribution for a sample proportion can be described as approximately normal.

  • UNC-3.M Interpret probabilities and parameters for a sampling distribution for a sample proportion.

5.1, 5.4, 5.5

1.A, 3.B, 3.C, 4.B

Notes 3 – Sampling Distribution of a Difference in Sample Proportions

  • UNC-3.N Determine parameters of a sampling distribution for a difference in sample proportions.

  • UNC-3.O Determine whether a sampling distribution for a difference of sample proportions can be described as approximately normal.

  • UNC-3.P Interpret probabilities and parameters for a sampling distribution for a difference in proportions.

5.6

3.B, 3.C, 4.B

Notes 4 – Sampling Distribution of a Sample Mean

  • UNC-3.H Estimate sampling distributions using simulation.

  • UNC-3.Q Determine parameters for a sampling distribution for sample means

  • UNC-3.R Determine whether a sampling distribution of a sample mean can be described as approximately normal.

  • UNC-3.S Interpret probabilities and parameters for a sampling distribution for a sample mean.

5.3, 5.7

3.B, 3.C, 4.B

Notes 5 – Sampling Distribution of a Difference in Sample Means

  • UNC-3.T Determine parameters of a sampling distribution for a difference in sample means

  • UNC-3.U Determine whether a sampling distribution of a difference in sample means can be described as approximately normal.

  • UNC-3.V Interpret probabilities and parameters for a sampling distribution for a difference in sample means

5.8

3.B, 3.C, 4.B



Unit Assessments*:

  • Unit 5 Quiz: 10 multiple choice questions and 1 free response question

  • Unit 5 Test: 15 multiple choice questions and 1 free response question

Unit Project: Normal Approximation for the Binomial*

  • Students explore how we can use the normal distribution as an approximation for the binomial when certain conditions are satisfied.

  • CED Skills: 3.A, 3.B, 3.C, 4.B




* Course sequence, assignments and assessments are subject to change.