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MATH Courses for School GPA STARPREP® MATHEMATICS PROGRAMSAP® Statistics

AP® Statistics is an introductory college-level statistics course that introduces students to the major concepts and tools for collecting, analyzing, and drawing conclusions from data. Students cultivate their understanding of statistics using technology, investigations, problem solving, and writing as they explore concepts like variation and distribution; patterns and uncertainty; and data-based predictions, decisions, and conclusions.

AP® Statistics

STARPREP®에서 제공하는 AP® Statistics 프로그램은 총 2개의 PHASES
(GPA-Boosting Course / 2023 MAY' TEST-PREP Course)으로 나뉘어지며 학생/반의 수준에 따라 진도가 정해집니다.

[학생의 성적/수업 이해도위주의 수업 진행]


for Graders 9-12
(STARPREP® course code: APSTA)


Professor
Dr. Jerome E Lee
MIT Mathematical Physics 졸업
KAIST Multi-physics 졸업
티칭 경력 23년차

Registration Board

High School AP® Statistics

  • Lecture Dates/Registration Status
  • Every Saturday
    9:00am-12:00pm
    starting from August 6, 2022

    Registration Status Open Registration Form 등록 신청서
  • AP® Statistics
  • Course Code/Professor(Alma Mater)
  • STARPREP® COURSE CODE : APSTA-01

    ★ AP® Statistics GPA-Boosting Course ★
    학교 내신점수향상 대비반

    Professor
    Dr. Jerome E Lee
    MIT Mathematical Physics 졸업
    KAIST Multi-physics 졸업
    티칭 경력 23년차
  • Features
  • ★ 2022-2023 AP® Statistics ★

    AP® Statistics GPA-Boosting Course
    학교 내신점수향상 대비반

    Students' Satisfaction : above 99%

    Optimizing Concurrent Classrooms
    (In the Classroom And Online Simultaneously)
  • AP® Statistics
Lecture Dates/Registration Status Course Code/Professor(Alma Mater) Features
Lecture Date
Every Saturday 9:00am-12:00pm
starting from August 6, 2022

Registration Status Open Registration Form 등록 신청서
STARPREP® COURSE CODE : APSTA-01

★ AP® Statistics GPA-Boosting Course ★
학교 내신점수향상 대비반

Professor
Dr. Jerome E Lee
MIT Mathematical Physics 졸업
KAIST Multi-physics 졸업
티칭 경력 23년차
★2022-2023 AP® Statistics ★

AP® Statistics GPA-Boosting Course
학교 내신점수향상 대비반

Students' Satisfaction : above 99%

Optimizing Concurrent Classrooms
(In the Classroom And Online Simultaneously)
AP® Statistics AP® Statistics

Curriculum Guide

High School AP® Statistics

01 One-Variable Data Analysis

1-1  Introducing Statistics: What Can We Learn from Data?
1-2  The Language of Variation: Variables
1-3  Representing a Categorical Variable with Tables
1-4  Representing a Categorical Variable with Graphs
1-5  Representing a Quantitative Variable with Graphs
1-6  Describing the Distribution of a Quantitative Variable
1-7  Summary Statistics for a Quantitative Variable
1-8  Graphical Representations of Summary Statistics
1-9  Comparing Distributions of a Quantitative Variable
1-10  The Normal Distribution
1-11  Review
1-12  Practice Problems
1-13  Cumulative Review Problems

02 Two-Variable Data Analysis

2-1  Introducing Statistics: Are Variables Related?
2-2  Representing Two Categorical Variables
2-3  Statistics for Two Categorical Variables
2-4  Representing the Relationship Between Two Quantitative Variables
2-5  Correlation
2-6  Linear Regression Models
2-7  Residuals
2-8  Least Squares Regression
2-9  Analyzing Departures from Linearity
2-10  Review
2-11  Practice Problems
2-12  Cumulative Review Problems

03 Collecting Data

3-1  Introducing Statistics: Do the Data We Collected Tell the Truth?
3-2  Introduction to Planning a Study
3-3  Random Sampling and Data Collection
3-4  Potential Problems with Sampling
3-5  Introduction to Experimental Design
3-6  Selecting an Experimental Design
3-7  Inference and Experiments
3-8  Review
3-9  Practice Problems
3-10  Cumulative Review Problems

04 Probability,Random Variables, and Probability Distributions

4-1  Introducing Statistics: Random and Non-Random Patterns?
4-2  Estimating Probabilities Using Simulation
4-3  Introduction to Probability
4-4  Mutually Exclusive Events
4-5  Conditional Probability
4-6  Independent Events and Unions of Events
4-7  Introduction to Random Variables and Probability Distributions
4-8  Mean and Standard Deviation of Random Variables
4-9  Combining Random Variables
4-10  Introduction to the Binomial Distribution
4-11  Parameters for a Binomial Distribution
4-12  The Geometric Distribution
4-13  Review
4-14  Practice Problems
4-15  Cumulative Review Problems

05 Sampling distributions

5-1  Introducing Statistics: Why Is My Sample Not Like Yours?
5-2  The Normal Distribution, Revisited
5-3  The Central Limit Theorem
5-4  Biased and Unbiased Point Estimates
5-5  Sampling Distributions for Sample Proportions
5-6  Sampling Distributions for Differences in Sample Proportions
5-7  Sampling Distributions for Sample Means
5-8  Sampling Distributions for Differences in Sample Means
5-9  Review
5-10  Practice Problems
5-11  Cumulative Review Problems

06 Inference for Categorical Data: Proportions

6-1  Introducing Statistics: Why Be Normal?
6-2  Constructing a Confidence Interval for a Population Proportion
6-3  Justifying a Claim Based on a Confidence Interval for a Population Proportion
6-4  Setting Up a Test for a Population Proportion
6-5  Interpreting p-Values
6-6  Concluding a Test for a Population Proportion
6-7  Potential Errors When Performing Tests
6-8  Confidence Intervals for the Difference of Two Proportion
6-9  Justifying a Claim Based on a Confidence Interval for a Difference of Population proportions
6-10  Setting Up a Test for the Difference of Two Population Proportions
6-11  Carrying Out a Test for the Difference of Two Population Proportions
6-12  Review
6-13  Practice Problems
6-14  Cumulative Review Problems

07 Inference for Quantitative Data: Means

7-1  Introducing Statistics: Should I Worry About Error?
7-2  Constructing a Confidence Interval for a Population Mean
7-3  Justifying a Claim About a Population Mean Based on a Confidence Interval
7-4  Setting Up a Test for a Population Mean
7- 5 Carrying Out a Test for a Population Mean
7-6  Confidence Intervals for the Difference of Two Means
7-7  Justifying a Claim About the Difference of Two Means Based on a Confidence Interval
7-8  Setting Up a Test for the Difference of Two Population Means
7-9  Carrying Out a Test for the Difference of Two Population Means
7-10  Skills Focus: Selecting, Implementing, and Communicating Inference Procedures
7-11  Review
7-12  Practice Problems
7-13  Cumulative Review Problems

08 Inference for Categorical Data: Chi-Square

8-1  Introducing Statistics: Are My Results Unexpected?
8-2  Setting Up a Chi-Square Goodness of Fit Test
8-3  Carrying Out a Chi-Square Test for Goodness of Fit
8-4  Expected Counts in Two-Way Tables
8-5  Setting Up a Chi-Square Test for Homogeneity or Independence
8-6  Carrying Out a Chi-Square Test for Homogeneity or Independence
8-7  Skills Focus: Selecting an Appropriate Inference Procedure for Categorical Data
8-8  Review
8-9  Practice Problems
8-10  Cumulative Review Problems

09 Inference for Quantitative Data: Slopes

9-1  Introducing Statistics: Do Those Points Align?
9-2  Confidence Intervals for the Slope of a Regression Model
9-3  Justifying a Claim About the Slope of a Regression Model Based on a Confidence Interval
9-4  Setting Up a Test for the Slope of a Regression Model
9-5  Carrying Out a Test for the Slope of a Regression Model
9-6  Skills Focus: Selecting an Appropriate Inference Procedure
9-7  Review
9-8  Practice Problems
9-9  Cumulative Review Problems

01 One-Variable Data Analysis

1-1  Introducing Statistics: What Can We Learn from Data?
1-2  The Language of Variation: Variables
1-3  Representing a Categorical Variable with Tables
1-4  Representing a Categorical Variable with Graphs
1-5  Representing a Quantitative Variable with Graphs
1-6  Describing the Distribution of a Quantitative Variable
1-7  Summary Statistics for a Quantitative Variable
1-8  Graphical Representations of Summary Statistics
1-9  Comparing Distributions of a Quantitative Variable
1-10  The Normal Distribution
1-11  Review
1-12  Practice Problems
1-13  Cumulative Review Problems

02 Two-Variable Data Analysis

2-1  Introducing Statistics: Are Variables Related?
2-2  Representing Two Categorical Variables
2-3  Statistics for Two Categorical Variables
2-4  Representing the Relationship Between Two Quantitative Variables
2-5  Correlation
2-6  Linear Regression Models
2-7  Residuals
2-8  Least Squares Regression
2-9  Analyzing Departures from Linearity
2-10  Review
2-11  Practice Problems
2-12  Cumulative Review Problems

03 Collecting Data

3-1  Introducing Statistics: Do the Data We Collected Tell the Truth?
3-2  Introduction to Planning a Study
3-3  Random Sampling and Data Collection
3-4  Potential Problems with Sampling
3-5  Introduction to Experimental Design
3-6  Selecting an Experimental Design
3-7  Inference and Experiments
3-8  Review
3-9  Practice Problems
3-10  Cumulative Review Problems

04 Probability,Random Variables, and Probability Distributions

4-1  Introducing Statistics: Random and Non-Random Patterns?
4-2  Estimating Probabilities Using Simulation
4-3  Introduction to Probability
4-4  Mutually Exclusive Events
4-5  Conditional Probability
4-6  Independent Events and Unions of Events
4-7  Introduction to Random Variables and Probability Distributions
4-8  Mean and Standard Deviation of Random Variables
4-9  Combining Random Variables
4-10  Introduction to the Binomial Distribution
4-11  Parameters for a Binomial Distribution
4-12  The Geometric Distribution
4-13  Review
4-14  Practice Problems
4-15  Cumulative Review Problems

05 Sampling distributions

5-1  Introducing Statistics: Why Is My Sample Not Like Yours?
5-2  The Normal Distribution, Revisited
5-3  The Central Limit Theorem
5-4  Biased and Unbiased Point Estimates
5-5  Sampling Distributions for Sample Proportions
5-6  Sampling Distributions for Differences in Sample Proportions
5-7  Sampling Distributions for Sample Means
5-8  Sampling Distributions for Differences in Sample Means
5-9  Review
5-10  Practice Problems
5-11  Cumulative Review Problems

06 Inference for Categorical Data: Proportions

6-1  Introducing Statistics: Why Be Normal?
6-2  Constructing a Confidence Interval for a Population Proportion
6-3  Justifying a Claim Based on a Confidence Interval for a Population Proportion
6-4  Setting Up a Test for a Population Proportion
6-5  Interpreting p-Values
6-6  Concluding a Test for a Population Proportion
6-7  Potential Errors When Performing Tests
6-8  Confidence Intervals for the Difference of Two Proportion
6-9  Justifying a Claim Based on a Confidence Interval for a Difference of Population proportions
6-10  Setting Up a Test for the Difference of Two Population Proportions
6-11  Carrying Out a Test for the Difference of Two Population Proportions
6-12  Review
6-13  Practice Problems
6-14  Cumulative Review Problems

07 Inference for Quantitative Data: Means

7-1  Introducing Statistics: Should I Worry About Error?
7-2  Constructing a Confidence Interval for a Population Mean
7-3  Justifying a Claim About a Population Mean Based on a Confidence Interval
7-4  Setting Up a Test for a Population Mean
7-5  Carrying Out a Test for a Population Mean
7-6  Confidence Intervals for the Difference of Two Means
7-7  Justifying a Claim About the Difference of Two Means Based on a Confidence Interval
7-8  Setting Up a Test for the Difference of Two Population Means
7-9  Carrying Out a Test for the Difference of Two Population Means
7-10  Skills Focus: Selecting, Implementing, and Communicating Inference Procedures
7-11  Review
7-12  Practice Problems
7-13  Cumulative Review Problems

08 Inference for Categorical Data: Chi-Square

8-1  Introducing Statistics: Are My Results Unexpected?
8-2  Setting Up a Chi-Square Goodness of Fit Test
8-3  Carrying Out a Chi-Square Test for Goodness of Fit
8-4  Expected Counts in Two-Way Tables
8-5  Setting Up a Chi-Square Test for Homogeneity or Independence
8-6  Carrying Out a Chi-Square Test for Homogeneity or Independence
8-7  Skills Focus: Selecting an Appropriate Inference Procedure for Categorical Data
8-8  Review
8-9  Practice Problems
8-10  Cumulative Review Problems

09 Inference for Quantitative Data: Slopes

9-1  Introducing Statistics: Do Those Points Align?
9-2  Confidence Intervals for the Slope of a Regression Model
9-3  Justifying a Claim About the Slope of a Regression Model Based on a Confidence Interval
9-4  Setting Up a Test for the Slope of a Regression Model
9-5  Carrying Out a Test for the Slope of a Regression Model
9-6  Skills Focus: Selecting an Appropriate Inference Procedure
9-7  Review
9-8  Practice Problems
9-9  Cumulative Review Problems

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Reference Lectures

AP® Statistics

Introduccing AP® Statistics AP® Statistics
Final Review on AP® Statistics Cram Review on AP® Statistics
Chi Square Goodness of Fit Test Linear Regression t-Test