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David Lillis

Member Training: Smoothing

by David Lillis Leave a Comment

Smoothing can assist data analysis by highlighting important trends and revealing long term movements in time series that otherwise can be hard to see.

Many data smoothing techniques have been developed, each of which may be useful for particular kinds of data and in specific applications. David will give an introductory overview of the most common smoothing methods, and will show examples of their use. He will cover moving averages, exponential smoothing, the Kalman Filter, low-pass filters, high pass filters, LOWESS and smoothing splines.

This presentation is pitched towards those who may use smoothing techniques during the course of their analytic work, but who have little familiarity with the techniques themselves. David will avoid the underpinning mathematical and statistical methods, but instead will focus on providing a clear understanding of what each technique is about.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

[Read more…] about Member Training: Smoothing

Tagged With: high pass filters, Kalman Filter, low-pass filters, LOWESS, smoothing, smoothing splines, time series

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Linear Models in R: Diagnosing Our Regression Model

by David Lillis 4 Comments

by David Lillis, Ph.D.

Last time we created two variables and added a best-fit regression line to our plot of the variables. Here are the two variables again. [Read more…] about Linear Models in R: Diagnosing Our Regression Model

Tagged With: diagnosis, lines, plots, plotting, R, Regression

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Member Training: Introduction to Time Series Analysis

by David Lillis 1 Comment

Time Series are economic or other data that are collected over an extended period of time. Many clever methods have been developed to analyze time series, both to understand the factors that cause variation and to forecast future values.

In this session, David will introduce us to time series analysis and explain some of the basic techniques for modelling time series and creating forecasts.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
Not a Member? Join!

About the Instructor

David LillisDavid Lillis is an applied statistician in Wellington, New Zealand.

His company, Sigma Statistics and Research Limited, provides online instruction, face-to-face workshops on R, and coding services in R.

David holds a doctorate in applied statistics and is a frequent contributor to The Analysis Factor, including our blog series R is Not So Hard.

 

Not a Member Yet?

It’s never too early to set yourself up for successful analysis with support and training from expert statisticians. Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 100+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.

Tagged With: time series

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  • Member Training: Smoothing
  • Member Training: Heterogeneity in Meta-analysis
  • Member Training: Matrix Algebra for Data Analysts: A Primer
  • Member Training: A (Gentle) Introduction to k-Nearest Neighbor

Member Training: Item Response Theory and Rasch Models

by David Lillis Leave a Comment

Item Response Theory (IRT) refers to a family of statistical models for evaluating the design and scoring of psychometric tests, assessments and surveys. It is used on assessments in psychology, psychometrics, education, health studies, marketing, economics and social sciences — assessments that involve categorical items (e.g., Likert items).

In this webinar, you will learn about:

  1. The key ideas and techniques of IRT, with examples from educational assessment
  2. The Rasch Model and the Graded Response Model — two of the most commonly-used IRT models
  3. A range of analytic techniques that should be used in conjunction with IRT

This webinar will introduce you to the basic ideas and applications of IRT, and show how you can acquire the skills necessary to conduct IRT analysis at the professional level.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
Not a Member? Join!

About the Instructor

David LillisDavid Lillis is an applied statistician in Wellington, New Zealand.

His company, Sigma Statistics and Research Limited, provides online instruction, face-to-face workshops on R, and coding services in R.

David holds a doctorate in applied statistics and is a frequent contributor to The Analysis Factor, including our blog series R is Not So Hard.

Not a Member Yet?

It’s never too early to set yourself up for successful analysis with support and training from expert statisticians. Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 100+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.

Tagged With: graded response model, item response theory, rasch model

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  • Member Training: Matrix Algebra for Data Analysts: A Primer
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This Month’s Statistically Speaking Live Training

  • Member Training: Analyzing Pre-Post Data

Upcoming Free Webinars

Poisson and Negative Binomial Regression Models for Count Data

Upcoming Workshops

  • Analyzing Count Data: Poisson, Negative Binomial, and Other Essential Models (Jul 2022)
  • Introduction to Generalized Linear Mixed Models (Jul 2022)

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