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Probability and Statistics (MTH413)

Probability and Statistics (MTH413)

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Quick Overview

In this high school math course, students learn counting methods, probability, descriptive statistics, graphs of data, the normal curve, statistical inference, and linear regression. Proficiency is measured through frequent online and offline assessments, as well as asynchronous discussions. Problem-solving activities provide an opportunity for students to demonstrate their skills in real world situations.

Teacher-Led Course (one-time payment)   $425.00

Monthly Fees: Due Today:

Price as configured: $0.00

Details

Course Overview

In this high school math course, students learn counting methods, probability, descriptive statistics, graphs of data, the normal curve, statistical inference, and linear regression. Proficiency is measured through frequent online and offline assessments, as well as asynchronous discussions. Problem-solving activities provide an opportunity for students to demonstrate their skills in real world situations.

Course Outline

Unit 1: Representing Data Graphically

Students develop skills and instincts that will allow them to create clear, convincing presentations of any data set they encounter. They also learn to look at any data chart or plot with a critical, mathematical eye and point out trends and important features of the data. They work on an extended graphing exercise throughout the unit and prepare a presentation. Topics include:

  • Course Introduction
  • Introduction: Representing Data Graphically
  • Data and Variables
  • Graphs of Categorical Data
  • Two-Way Tables
  • Line Plots
  • Frequency Tables
  • Histograms
  • Stem-and-Leaf Plots
  • Time Series Plots

Unit 2: Representing Data Numerically

Students work with real data from 55 national parks in the United States, learning how to represent an entire set of data by using single numbers that describe where the center of the distribution is located and how the data are spread. Topics include:

  • Introduction: Representing Data Numerically
  • Measures of Center
  • Box Plots
  • Determining Quartiles
  • Outliers
  • Comparing Data Sets
  • Measuring Spread
  • Transforming Data Sets

Unit 3. Counting and Probability

Students learn mathematical formulas for counting large sets and determine the number of combinations and arrangements. They also learn basic probability and the difference between experimental and theoretical probability. Topics include:

  • Introduction: Counting and Probability
  • Counting Methods
  • Permutations
  • Combinations
  • Basic Probability
  • Geometric Probability
  • Mutually Exclusive Events
  • Overlapping Events
  • Independent and Dependent Events
  • Experimental Probability

Unit 4. Random Variables and Distributions

Students begin to develop a more keen understanding of descriptive statistics. Topics include:

  • Introduction: Random Variables and Distributions
  • Creating Probability Distributions
  • Interpreting Probability Distributions
  • Expected Value
  • Binomial Distributions
  • Continuous Random Variables
  • The Normal Distribution
  • Standardizing Data
  • Comparing Scores
  • The Standard Normal Curve
  • Finding Standard Scores

Unit 5. Sampling

Students begin to learn about sampling and how to apply statistical methods to valid samples. Topics include:

  • Introduction: Sampling
  • Sample and Population
  • Bias in Sampling
  • Reducing Bias
  • Statistics and Parameters
  • Interval Estimates

Unit 6. Statistical Inference

Students learn how to put the power of statistics to work. Topics include:

  • Introduction: Statistical Inference
  • The Central Limit Theorem
  • Estimating Means
  • Mean Differences
  • Estimating Proportions
  • Proportion Differences

Unit 7. Relationships between Variables

Students learn how to identify and describe relationships between variables. Topics include:

  • Introduction: Relationships Between Variables
  • Scatter Plots
  • Association
  • The Correlation Coefficient
  • Fitting a Line to Data
  • Least Squares Regression
  • Regression Analysis
  • Cautions in Statistics

Unit 8: Semester Review and Test

Students review what they have learned and take the semester exam.

  • Semester Review
  • Semester Test

Additional Information

Course Length 4 Months
Prerequisites N/A
Course Materials No
Course Start Date

Courses Taught by a K12 Teacher

Courses with a teacher have designated start dates throughout Fall, Spring, and Summer. Full-year courses last 10 months and semester courses last 4 months. Courses are taught by teachers in K12 International Academy. For details on start dates, click here.

Teacher Assisted Yes, this course is taught by a K12 International Academy teacher. If you are looking for a teacher-supported option with additional flexibility and year-round start dates, click here to learn about the Keystone School, another K12 online private schooling option.
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To use this course, you'll need a computer with an Internet connection.  Some courses require additional free software programs, which you can download from the Internet.

Hardware and Browsers (Minimum Recommendations)

Windows OS

  • CPU: 1.8 GHz or faster processor (or equivalent)

  • RAM: 1GB of RAM

  • Browser: Microsoft Internet Explorer 9.0 or higher, Mozilla Firefox 10.0 versions or higher, Chrome 17.0 or higher

  • At this time our users are encouraged not to upgrade to Windows 10 or Edge (the new browser)

 

Mac OS

  • CPU: PowerPC G4 1 GHz or faster processor; Intel Core Duo 1.83 GHz or faster processor

  • RAM: 1GB of RAM

  • Browser: Firefox 10.0 versions or higher, Chrome 17.0 or higher (Safari is not supported!)

Internet Connections

It is highly recommended that a broadband connection be used instead of dial up.