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Syllabus Title:
Statistics
Syllabus Description:

Data, data, everywhere you go! Information has gone from scarce to superabundant thanks to the powers of the internet and computing. But all this data means nothing without the ability to transform it in into something useful. Enter statistics. Everyone from crime analysts to journalists, Fortune 500 CEOs to insurance agents rely on statistics to analyze the information they need to make the best decisions. This class will give you the methods and know-how you need to discern probabilities, understand variables, and accurately measure and display data. In-depth labs and activities will help you soak up the entire statistical process including design, analysis, and conclusions. Prerequisite: Successful completion of Algebra I.

Collection Semester:
SEMESTER 1
New Unit Collection:
Section 1: Describing Distributions with Graphs for Univariate Data
New Unit Content:
• 1.1 Pie Charts and Bar Charts
• 1.2 Describing Graphs
• 1.3 Dotplots
• 1.4 Stemplots
• 1.5 Comparing Graphs
• 1.6 Histograms
• 1.7 Ogives
• 1.8 Calculator Lesson: Graphing Univariate Graphs
Section 2: Describing Distributions with Numbers (Statistics)
New Unit Content:
• 2.1 Measures of Center
• 2.2 Measures of Spread Part 1
• 2.3 Measures of Spread Part 2
• 2.4 Outliers
• 2.5 Box and Whisker Plots
• 2.6 Comparing Distributions Again
• 2.7 Boxplot/Histogram Exploration
Section 3: Density Curves
New Unit Content:
• 3.1 Uniform Density Curves
• 3.2 Funky Figures
• 3.3 Mean vs Median
Section 4: Normal Distributions
New Unit Content:
• 4.1 Standardization (z-scores)
• 4.2 What is a Normal Curve?
• 4.3 Empirical Rule
• 4.4 z-scores Revisited
• 4.5 More Normal Distribution
• 4.6 Is the Data Normal?
• 4.7 Calculator Lesson: normalcdf and invNorm
Section 5: Scatterplots and Correlation
New Unit Content:
• 5.1 Scatterplots
• 5.2 Correlation
Section 6: Least Squares Regression
New Unit Content:
• 6.1 What is an LSRL?
• 6.2 Interpreting Slope and y-intercept
• 6.3 Finding and Interpreting the Correlation Coefficient (r)
• 6.4 More Ways to Find the LSRL
• 6.5 More Ways to Find the LSRL Part 2
Section 7: Predicting, Residuals and r^2
New Unit Content:
• 7.1 Predicting and Residuals
• 7.2 Coefficient of Determination (r^2)
• 7.3 Linear Regression: Putting It Together
• 7.4 Residual Plots
Section 8: Transforming Non-Linear Data
New Unit Content:
• 8.1 Exponential Data
• 8.2 Power Data
• 8.3 Residual Plots Revisited
Section 9: Sampling and Bias
New Unit Content:
• 9.1 Bad Samples
• 9.2 Types of Bias
• 9.3 Good Samples = Random Samples
• 9.4 Using Random Numbers for Sampling
Section 10: Experiments
New Unit Content:
• 10.1 Key Terms in Experimental Design
• 10.2 Completely Randomized Design
• 10.3 Block Design
• 10.4 Matched Pairs
Section 11: Simulation
New Unit Content:
• 11.1 Simulation
• 11.2 Simulation Practice
Section 12: General Probability Rules
New Unit Content:
• 12.1 Key Terms and Ideas
• 12.2 Formulas on the AP Exam
Section 13: Independent and Disjoint Events
New Unit Content:
• 13.1 Disjoint Events
• 13.2 Independent Events
• 13.3 Venn Diagrams
Section 14: Two-Ways Tables and Conditional Probability
New Unit Content:
• 14.1 Two Way Tables
• 14.2 Conditional Probability
• 14.3 Independence Revisited
Section 15: Discrete Random Variables
New Unit Content:
• 15.1 Probability Distributions for Random Variables
• 15.2 Mean and Standard Deviation of Discrete Random Variables
• 15.3 Rules for Means
• 15.4 Rules for Variances
Section 16: Binomial Distributions
New Unit Content:
• 16.1 Binomial Distribution Part 1
• 16.2 Binomial Distribution Part 2
• 16.3 Mean and Standard Deviation of Binomial Distributions
Section 17: Geometric Distributions
New Unit Content:
• 17.1 Geometric Distribution Part 1
• 17.2 Geometric Distribution Part 2
• 17.3 Mean of Geometric Distributions
• 17.4 Binomial, Geometric and Normal Exploration
SEMESTER 2
New Unit Collection:
Section 18: Continuous Random Variables
New Unit Content:
• 18.0 Introduction
• 18.1 Funky Figures Revisited
• 18.2 Normal Distribution Review
Section 19: Sampling Distributions - Means
New Unit Content:
• 19.1 Overview of Sampling Distributions
• 19.2 Sampling Distribution for x-bar
• 19.3 Central Limit Theorem
Section 20: Sampling Distributions - Proportions
New Unit Content:
• 20.1 Sampling Distribution for p-hat
• 20.2 Conditions for Inference - Proportions
• 20.3 Review
Unit 8: Confidence intervals for One-Sample Data
New Unit Content:
• Section 21: Confidence Intervals for a Mean - the z-interval
• 21.0 Introduction
• 21.1 Structure of a Confidence Interval
• 21.2 Confidence Interval for a Single Mean (z-interval)
• 21.3 Practice with Confidence Intervals for a Single Mean (z-interval)
Section 22: Confidence Intervals for a Mean - the t-interval
New Unit Content:
• 22.1 What is a t-distribution?
• 22.2 Confidence Interval for a Single Mean (t-interval)
• 22.3 Matched Pairs t-interval
• 22.4 Calculator Lesson: t-interval
Section 23: Confidence Intervals for One Proportion - the 1-proportion z-interval
New Unit Content:
• 23.1 Confidence Interval for Single Proportion (1-proportion z-interval)
• 23.2 Calculator Lesson: 1-proportion z-interval
• 23.3 Confidence Level and Finding n
• 23.4 Review
Section 24: Significance Tests - the Structure
New Unit Content:
• 24.0 Introduction
• 24.1 Structure of a Test Part 1
• 24.2 Structure of a Test Part 2
• Section 25: Significance Test for a Single Mean - the t-test
Section 25: Significance Test for a Single Mean - the t-test
New Unit Content:
• 25.1 One Sample t-test for Means (The Mechanics)
• 25.2 One Sample t-test for Means (Complete Test)
• 25.4 One Sample t-test for Means (Matched Pairs)
Section 26: Significance Test for One Proportion - the 1-proportion z-test
New Unit Content:
• 26.1 One Sample z-test for Proportions (The Mechanics)
• 26.2 One Sample z-test for Proportions (Complete Test)
• 26.3 Calculator Lesson: One Sample z-test for Proportions
Section 27: Errors and Power
New Unit Content:
• 27.1 Significance Level and Overview of Errors
• 27.2 Type I and Type II Errors
• 27.3 Power
• 27.4 Review
• 27.5 Hypothesis Tests and Confidence Intervals
Section 28: Two-Sample Inference for Two Independent Samples - Mean
New Unit Content:
• 28.0 Introduction
• 28.1 Two-Sample t-interval for Means
• 28.2 Calculator Lesson: Two-sample t-interval
• 28.3 Two-Sample t-test for Means
• 28.4 Calculator Lesson: Two-Sample t-test for Means
Section 29: Two -Sample Inference for Two Independent Samples - Proportion
New Unit Content:
• 29.1 Two-Sample z-interval for Proportions
• 29.2 Calculator Lesson: Two-Sample z-interval for Proportions
• 29.3 Two-Sample z-test for Proportions
• 29.4 Calculator Lesson: Two-Sample z-test for Proportions
• 29.5 Review
Section 30: Chi-Square Goodness of Fit Test
New Unit Content:
• 30.0 Introduction
• 30.1 Chi-Square Goodness of Fit Test - The Components
• 30.2 Chi-Square Goodness of Fit Test - The Complete Test
• 30.3 Calculator Lesson: Chi-Square Goodness of Fit Test
Section 31: Chi-Square Test for Independence and Homogeneity
New Unit Content:
• 31.1 Review of Two-Way Tables
• 31.2 Chi-Square Test for Independence - The Components
• 31.3 Chi-Square Test for Independence - The Complete Test
• 31.4 Calculator Lesson: Chi-Square Test for Independence
• 31.5 Review
Section 32: Confidence Interval for Slope
New Unit Content:
• 32.0 Introduction
• 32.1 Review of Linear Regression
• 32.2 Conditions for Inference for Slope
• 32.3 Linear Regression t-interval
• 32.4 Calculator Lesson: Linear Regression t-interval