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Modeling Data for Inference

This Modeling Data for Inference course teaches attendees how to use Python to perform causal inference on observational data. Participants learn how to work with inferential models, missing data,...

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Duration 5 days
Course Code DATA-142
Available Formats Classroom

Overview

This Modeling Data for Inference course teaches attendees how to use Python to perform causal inference on observational data. Participants learn how to work with inferential models, missing data, and experimental design.

Skills Gained

  • Perform causal inference in observational data using Python
  • Perform and interpret null hypothesis testing in Python
  • Implement generalized linear models in statsmodels
  • Understand missing data
  • Impute missing data
  • Generate accurate power calculations
  • Implement non-parametric methods to test hypotheses.
  • Use causal inference frameworks to identify causal effects from observational data

Prerequisites

Attendees must have a solid foundation in Python programming for descriptive analytics.

Course Details

Training Materials

All Data Modeling training students receive comprehensive courseware.

Software Requirements

  • Windows, Mac, or Linux
  • A current version of Anaconda for Python 3.x, or a comparable Python installation with the necessary libraries (Ascendient Learning can provide a list)

Outline

  • Introduction
  • GLMs with Python using Stats Models
    • Applying Statistical Models for Analysis in Python: The A/B test
      • Explanation of statsmodels library of functions
      • Inferential and descriptive statistics refresher
      • Implementing A/B tests
  • Modeling Continuous Data (Linear models)
    • Formulation of the simple linear model
    • Application of the intercept only, null model
      • Binary predictor
      • Interpreting results
      • Categorical predictor
      • Continuous predictor
      • Polynomial expansions
      • Multiple linear regression
      • Spline models
      • Interaction terms
      • Picking the “best” model
      • Discussion of confounding, interaction terms, and model building approaches
    • Modeling Binary Data (Logistic models)
      • Discussion of the generalized linear model
      • The Logit link function
      • Binomial distribution
      • Intercept only model
      • Back transformation of coefficients
      • Simple predictor
      • Multiple predictors
      • Odds ratio interpretations
      • Generating a scoring data set
      • Predicting from the model with new data
    • Modeling Count Outcomes
      • How are count outcomes different?
      • Poisson models
      • Over dispersed modeling options
      • Log link functions
      • Using offsets to model rates / uneven follow-up
  • Power Analyses/Study Design
    • Understanding and estimating statistical power
    • Type 1 and type 2 errors
    • Using existing power estimators
    • Simulating power through the data-generating process
  • Non-Parametric Analysis Methods
    • Using bootstrapping/permutation tests
      • Bootstrapping versus depending on asymptotic behavior to estimate confidence intervals
      • How different/stable are my results?
      • resampling a data set
      • bias-corrected bootstrap interval
      • Extending the bootstrap function to calculate more statistics
      • Permutation tests for p-values
  • Missing data
    • Quantifying
    • Visualizing missing data
    • MAR,MCAR,MNAR
    • Sensitivity analysis
    • Imputation
      • MICE/trees pre-processing
  • Time to Event (Survival) Analysis
    • Visualizing Hazards Across Time
    • Understanding the Log Rank Test
    • Cox Proportional Hazards Modeling
      • Understanding and interpreting the Hazard Ratio
      • Model diagnostics and assumptions
      • Implementing Time Varying Covariates
    • Parametric Survival Models
      • Weibull Model
      • Exponential Model
      • Predicting Failure Times
  • Causal Inference: The Potential Outcomes Framework
    • Defining treatment effects (ATT, ATE)
    • Identifying populations of interest
    • Defining your causal hypothesis
    • Understanding the counterfactual
    • Establishing the causal diagram for your problem
    • Different methods for conditioning on variables:
      • Propensity Scores
      • Direct regression adjustment
      • G-computation formulas
    • Instrumental variable analysis
  • Conclusion
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Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

Contact Information

FAQ

Does the course schedule include a Lunchbreak?

Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

What does GTR stand for?

GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.

Does Ascendient Learning deliver group training?

Yes, we provide training for groups, individuals and private on sites. View our group training page for more information.

What does vendor-authorized training mean?

As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.

Is the training too basic, or will you go deep into technology?

It depends on your requirements, your role in your company, and your depth of knowledge. The good news about many of our learning paths, you can start from the fundamentals to highly specialized training.

How up-to-date are your courses and support materials?

We continuously work with our vendors to evaluate and refresh course material to reflect the latest training courses and best practices.

Are your instructors seasoned trainers who have deep knowledge of the training topic?

Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.

Do you provide hands-on training and exercises in an actual lab environment?

Lab access is dependent on the vendor and the type of training you sign up for. However, many of our top vendors will provide lab access to students to test and practice. The course description will specify lab access.

Will you customize the training for our company’s specific needs and goals?

We will work with you to identify training needs and areas of growth.  We offer a variety of training methods, such as private group training, on-site of your choice, and virtually. We provide courses and certifications that are aligned with your business goals.

How do I get started with certification?

Getting started on a certification pathway depends on your goals and the vendor you choose to get certified in. Many vendors offer entry-level IT certification to advanced IT certification that can boost your career. To get access to certification vouchers and discounts, please contact info@ascendientlearning.com.

Will I get access to content after I complete a course?

You will get access to the PDF of course books and guides, but access to the recording and slides will depend on the vendor and type of training you receive.

How do I request a W9 for Ascendient Learning?

View our filing status and how to request a W9.

Reviews

I was very pleased with the course setup by ExitCertified and the instructor.

Great instructor, clear and concise course. Labs were easy to follow and worked perfectly.

Both course material and instructor demonstrated a sound foundation on Maximo material

Good course. I appreciate the time the instructor put into teaching this class.

Provided good amount of material and a great instructor to teach the material.