Skip to content

Explore Courses | Elder Research | Contact | LMS Login

Statistics.com Logo
  • Courses
    • See All Courses
    • Calendar
    • Intro stats for college credit
    • Faculty
    • Group training
    • Credit & Credentialing
    • Teach With Us
  • Programs/Degrees
    • Certificates
      • Analytics for Data Science
      • Biostatistics
      • Programming For Data Science – Python (Experienced)
      • Programming For Data Science – Python (Novice)
      • Programming For Data Science – R (Experienced)
      • Programming For Data Science – R (Novice)
      • Social Science
    • Undergraduate Degree Programs
    • Graduate Degree Programs
    • Massive Open Online Courses (MOOC)
  • Partnerships
    • Higher Education
    • Enterprise
  • Resources
    • About Us
    • Blog
    • Word Of The Week
    • News and Announcements
    • Newsletter signup
    • Glossary
    • Statistical Symbols
    • FAQs & Knowledge Base
    • Testimonials
    • Test Yourself
Menu
  • Courses
    • See All Courses
    • Calendar
    • Intro stats for college credit
    • Faculty
    • Group training
    • Credit & Credentialing
    • Teach With Us
  • Programs/Degrees
    • Certificates
      • Analytics for Data Science
      • Biostatistics
      • Programming For Data Science – Python (Experienced)
      • Programming For Data Science – Python (Novice)
      • Programming For Data Science – R (Experienced)
      • Programming For Data Science – R (Novice)
      • Social Science
    • Undergraduate Degree Programs
    • Graduate Degree Programs
    • Massive Open Online Courses (MOOC)
  • Partnerships
    • Higher Education
    • Enterprise
  • Resources
    • About Us
    • Blog
    • Word Of The Week
    • News and Announcements
    • Newsletter signup
    • Glossary
    • Statistical Symbols
    • FAQs & Knowledge Base
    • Testimonials
    • Test Yourself
Student Login

Blog

Home Blog Aug 13: Statistics in Practice

Aug 13: Statistics in Practice

Statistics in Practice

This week we discuss the distinction between explanatory and predictive modeling and spotlight the workhorses of statistical modeling:

  • Oct 4 – Nov 1: Regression Analysis
  • Oct 4 – Nov 1: Categorical Data Analysis

See you in class!

– Peter Bruce,
Chief Academic Officer, Author, Instructor, and Founder

The Institute for Statistics Education at Statistics.com


Explain or Predict?

Are you flummoxed by the profusion of assessment metrics for statistical models like linear regression? Typical multiple linear regression output will contain, in addition to a distribution of errors (residuals) and RMSE (root mean squared error), such values as R-squared, adjusted R-squared, t-statistics, F-statistics, P-values, degrees of freedom, plus more. How do you make sense of them all? […]


Problem of the Week

The Second Heads

A friend tosses two coins, and you ask “Is one of them a heads?” The friend replies “Yes.” What is the probability that the other is a heads? […]


Course Spotlight

These two courses cover the workhorses of statistical modeling, multiple linear regression and logistic regression.

Oct 4 – Nov 1: Regression Analysis

Regression Analysis is taught by Iain Pardoe, the author of Applied Regression Modeling, the popular text that is used in the course.

In Regression Analysis, you will learn how to

  • Calculate a simple linear regression model, assess its performance and check assumptions
  • Extend the model to multiple linear regression
  • Transform predictors and response variables to improve model fit
  • Deal with qualitative predictors, interactions and influential points

Oct 4 – Nov 1: Categorical Data Analysis

Categorical Data Analysis is taught by Brian Marx, Professor of Statistics at Louisiana State University, coordinating editor of Statistical Modelling: An International Journal, and co-author or co-editor of several books on statistical modeling.

In Categorical Data Analysis you will learn how to

  • Work with RxC tables and test for independence, and equality of proportions
  • Fit logistic models for binary data
  • Fit Poisson models for count data

See you in class!


Regression Analysis

Digital Badges

Endorsed by the American Council on Education

Statistics.com is committed to providing you with the tools necessary to achieve your professional goals. Digital badges represent your skills and abilities and provide a way of sharing them online in a simple, trusted and verifiable way.


Contact Us To Register or Learn More

If you have any questions on our courses, certificates, and degree programs and how they can apply to you, your work, and to your career, please get in touch. We’re here to help you succeed.

Recent Posts

  • Oct 6: Ethical AI: Darth Vader and the Cowardly Lion
    /
    0 Comments
  • Oct 19: Data Literacy – The Chainsaw Case
    /
    0 Comments
  • Data Literacy – The Chainsaw Case
    /
    0 Comments

About Statistics.com

Statistics.com offers academic and professional education in statistics, analytics, and data science at beginner, intermediate, and advanced levels of instruction. Statistics.com is a part of Elder Research, a data science consultancy with 25 years of experience in data analytics.

 The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV)

Our Links

  • Contact Us
  • Site Map
  • Explore Courses
  • About Us
  • Management Team
  • Contact Us
  • Site Map
  • Explore Courses
  • About Us
  • Management Team

Social Networks

Facebook Twitter Youtube Linkedin

Contact

The Institute for Statistics Education
2107 Wilson Blvd
Suite 850 
Arlington, VA 22201
(571) 281-8817

ourcourses@statistics.com

  • Contact Us
  • Site Map
  • Explore Courses
  • About Us
  • Management Team

© Copyright 2023 - Statistics.com, LLC | All Rights Reserved | Privacy Policy | Terms of Use

By continuing to use this website, you consent to the use of cookies in accordance with our Cookie Policy.

Accept