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MAT 1372 Course Hub

Mathematics Department Course Hub

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    • WeBWorK – Faculty Resources
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  • Project Profile
  • Home
  • About
  • Course Outline
  • Lessons
  • Resources
    • Textbook
    • WeBWorK through Rederly
    • Video resources
    • Tutoring
    • Review
  • For Faculty
    • Faculty Announcements
    • Course Coordination
    • WeBWorK – Faculty Resources
    • Training and Support

Lessons

  • Lesson #1: Introduction to Statistics and Excel
  • Lesson #2: Graphical Descriptive Techniques
  • Lesson #3: Measures of Central Location and Variability
  • Lesson #4: Covariance and Coefficient of Correlation
  • Lesson #5: Least Squares Method and Regression
  • Lesson #6: Assigning Probabilities to Events; Probability Rules
  • Lesson #7: Experiments Having Equally Likely Outcomes
  • Lesson #8: Conditional Probability and Independence
  • Lesson #9: Relative Frequency Distribution and z-scores
  • Lesson #10: Random Variables, Probability Distributions
  • Lesson #11: Expected Value and Variance
  • Lesson #12: Binomial Distribution
  • Lesson #13: Poisson Distribution
  • Lesson #14: Continuous Random Variables
  • Lesson #15: Normal Random Variables
  • Lesson #16: Finding Normal Probabilities
  • Lessons #17 & #18: Sample Mean and Distribution of Sample Mean
  • Lesson #19: Distribution of the Sample Variance of a Normal Population
  • Lesson #20: Estimating Population Means
  • Lesson #21: Hypothesis Testing with Known Standard Deviation
  • Lesson #22: Inference about a Population Mean with Unknown Standard Deviation
  • Lesson #23: Chi-Squared Goodness of Fit Test
  • Lesson #24: Chi-Squared Test for Independence -Contingency Table

Lessons Menu

  • Lesson 1: Introduction to Statistics and Excel
  • Lesson 2: Graphical Descriptive Techniques
  • Lesson 3: Measures of Central Location and Variability
  • Lesson 4: Covariance and Coefficient of Correlation
  • Lesson 5: Least Squares Method and Regression
  • Lesson 6: Assigning Probabilities to Events; Probability Rules
  • Lesson 7: Experiments Having Equally Likely Outcomes
  • Lesson 8: Conditional Probability and Independence
  • Lesson 9: Relative Frequency Distribution and z-scores
  • Lesson 10: Random Variables, Probability Distributions
  • Lesson 11: Expected Value and Variance
  • Lesson 12: Binomial Distribution
  • Lesson 13: Poisson Distribution
  • Lesson 14: Continuous Random Variables
  • Lesson 15: Normal Random Variables
  • Lesson 16: Finding Normal Probabilities
  • Lessons 17 and 18: Sample Mean and Distribution of Sample Means
  • Lesson 19: Distribution of the Sample Variance of a Normal Population
  • Lesson 20: Estimating Population Means
  • Lesson 21: Hypothesis Testing with Known Standard Deviation
  • Lesson 22: Inference about a Population Mean with Unknown Standard Deviation
  • Lesson 23: Chi-Squared Goodness of Fit Test
  • Lesson 24: Chi-Square Test for Independence – Contingency Table

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The OpenLab at City Tech:A place to learn, work, and share

The OpenLab is an open-source, digital platform designed to support teaching and learning at City Tech (New York City College of Technology), and to promote student and faculty engagement in the intellectual and social life of the college community.

New York City College of Technology City University of New York

New York City College of Technology | City University of New York

Support

Help | Contact Us | Privacy Policy | Terms of Use | Credits

Accessibility

Our goal is to make the OpenLab accessible for all users.

Learn more about accessibility on the OpenLab

Copyright

Creative Commons

  • - Attribution
  • - NonCommercial
  • - ShareAlike
Creative Commons

© New York City College of Technology | City University of New York

MAT 1372 Course Hub