If you've had some statistics and feel that
mathematical notation and formulas are not your friend, consider Dr. Vittorio
Addona's online course Introduction to Statistical Modeling at
statistics.com.
This course provides a solid introduction to
the ideas and techniques of statistical modeling. Once you have completed this
course, you will be able to construct and interpret linear statistical models
involving multiple variables and co-variates, you will understand the
implications of including or excluding explanatory variables, you will be able
to conduct and interpret analysis of variance (ANOVA) and of covariance
(ANCOVA), and you will have a solid theoretical foundation for understanding
linear regression and experimental design. For more details please visit at http://www.statistics.com/ModelingIntro/.
Who Should Take This Course:
Students who are planning to take regression
and other modeling courses at statistics.com. Analysts or educators who need to
work with multiple variables but are not comfortable with the standard formula-
and linear-algebra based approach generally taken.
Course Program:
Course outline: The course
is structured as follows
SESSION 1: What is a Statistical
Model?
- Explanatory
and response variables
- Model
terms
- Reading
model formulas
- Fitting
models to data
- Introduction
to R software
SESSION 2: The Logic Behind
Models
- Statistical
adjustment
- Introduction
to the geometry of model fitting:
- case space vs variable space
- variables as vectors
- simple projection and least squares
- the model triangle
- Correlation
as a measure of alignment
SESSION 3: Randomness and Models
- Geometry
of multiple explanatory variables
- Random
walks and random directions
- Confidence
intervals
- Collinearity
SESSION 4: Inference and Models
- The
F statistic
- Decomposing
variance into parts
- Ambiguities
introduced by collinearity
- The
virtues of orthogonality
Homework:
The homework in this course consists of short
answer questions to test concepts, guided data analysis problems using
software, and guided data modeling problems using software.
In addition to assigned readings, this course
also has supplemental readings available online, and example software codes.
The Instructor, Dr. Vittorio Addona,
teaches statistics at Macalaster College in Minnesota. His research falls into three broad
categories: survival analysis, sports statistics, and election audits. His doctoral work was in survival analysis, a
statistical field often employed in medical studies of time-to-event data. Vittorio
teaches across the statistics curriculum: introductory modeling, probability,
mathematical statistics, and an applied survival analysis course.
This course takes place online at the
Institute for 4 weeks. During each course week, you participate at times of
your own choosing - there are no set times when you must be online. Course
participants will be given access to a private discussion board. In class
discussions led by the instructor, you can post questions, seek clarification, and
interact with your fellow students and the instructor.
The course typically requires 15 hours per
week. At the beginning of each week, you receive the relevant material, in
addition to answers to exercises from the previous session. During the week,
you are expected to go over the course materials, work through exercises, and
submit answers. Discussion among participants is encouraged. The instructor
will provide answers and comments, and at the end of the week, you will receive
individual feedback on your homework answers.
We, the Center for eLearning and Training
(C-eLT), Pune, partner with Statistics.com and offer these courses to Indian
participants at special prices payable in INR.
Call: 020 6680 0300 / 322
Websites:
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