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 July 28: Statistics in Practice

July 28: Statistics in Practice

Statistics in Practice

In this week’s brief we discuss outliers and anomalies, the unusual cases and events that often end up being the focus of attention. Our course spotlight is

  • Nov 6 – Dec 4: Anomaly Detection

If you’re interested in this topic, you should also consider the that it is part of. The methods and tools of anomaly detection are a collection of various data science techniques and you’ll get the most out of the Anomaly Detection course if you’ve had a broader preparation.

See you in class!

Peter Bruce

Founder, Author, and Senior Scientist

Statistics Logo


When Outliers are Central

In the wake of the 2008 recession, the government reported that average wages for all workers declined $384 from 2008 to 2009. Later, it amended this report to say the drop was really $598, due to errors in some tax returns. In a workforce of more than 140 million workers, can you guess how many taxpayers were responsible for this 56% “error?” Hint – you can count them on one […]


Word of the Week:

Bag-of-Words

In text mining, the term “bag-of-words” refers to the approach in which you consider a document simply as a collection of disconnected words. The analysis that follows does not rely on making sense of phrases or sentences, it simply makes use of the matrix of word occurrence frequency. The goal is classification or clustering of large numbers of documents using predictive models or clustering algorithms. Obviously, the bag-of-words technique cannot be used to interpret or make sense of a single document. However, in looking at numerous documents it can detect concepts (or topics) that involve multiple words.


Course Spotlight

Our spotlight this week is on the Anomaly Detection course, and the Programming For Data Science certificate programs of which it is part. You can take the course on its own, or as part of the 10-course certificate.

Nov 6 – Dec 4: Anomaly Detection

  • Use a supervised classification technique for anomaly detection, and understand the limits of supervised learning for anomaly detection
  • Apply a nearest-neighbor algorithm, and other unsupervised methods, for identifying anomalies in the absence of labels
  • Practice applying the various techniques to different problems in different domains
  • Assess which methods among a diverse set work best in a given situation

See you in class!


Certificate Spotlight

Programming for Data Science

The is your ticket into the world of data science and analytics. In this 18-month program (more or less, depending on your schedule), you’ll learn Python programming or R programming (or both, if you are ambitious), and learn how to

  • Read, understand, modify, and create basic functions
  • Manipulate data programmatically for data analytics and data mining
  • Extract data from a relational database using SQL, and merge it into a single file
  • Extract, clean, prepare, and mine data
  • Understand and implement predictive models: classification and prediction
  • Understand and implement unsupervised techniques such as clustering and recommender systems

A number of case-study projects are included and you can assemble a portfolio of your work. We have different program flavors, depending on your experience and your preference for R or Python. Intro stats is a prerequisite, but if you need it we’ll provide that course free of charge. We offer rolling admissions year-round – read more here.

See you in class!


Digital Badges

Anomaly Detection

Digital badges provide employers and peers concrete evidence of what you have learned and the skills required to earn your credential. Each badge’s digital image holds verified metadata describing your qualifications and the mastery required to earn them.


Contact Us To 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