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Multinomial

When Linear Models Don’t Fit Your Data, Now What?

by Karen Grace-Martin  32 Comments

When your dependent variable is not continuous, unbounded, and measured on an interval or ratio scale, linear models don’t fit. The data just will not meet the assumptions of linear models. But there’s good news, other models exist for many types of dependent variables.

Today I’m going to go into more detail about 6 common types of dependent variables that are either discrete, bounded, or measured on a nominal or ordinal scale and the tests that work for them instead. Some are all of these.

[Read more…] about When Linear Models Don’t Fit Your Data, Now What?

Tagged With: binary variable, categorical variable, Censored, dependent variable, Discrete Counts, Multinomial, ordinal variable, Poisson Regression, Proportion, Proportional Odds Model, regression models, Truncated, Zero Inflated

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  • 6 Types of Dependent Variables that will Never Meet the Linear Model Normality Assumption
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  • When to Check Model Assumptions
  • Proportions as Dependent Variable in Regression–Which Type of Model?

Member Training: Making Sense of Statistical Distributions

by guest contributer  Leave a Comment

Many who work with statistics are already functionally familiar with the normal distribution, and maybe even the binomial distribution.

These common distributions are helpful in many applications, but what happens when they just don’t work?

This webinar will cover a number of statistical distributions, including the:

  • Poisson and negative binomial distributions (especially useful for count data)
  • Multinomial distribution (for responses with more than two categories)
  • Beta distribution (for continuous percentages)
  • Gamma distribution (for right-skewed continuous data)
  • Bernoulli and binomial distributions (for probabilities and proportions)
  • And more!

We’ll also explore the relationships among statistical distributions, including those you may already use, like the normal, t, chi-squared, and F distributions.


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: Making Sense of Statistical Distributions

Tagged With: Bernoulli, beta, binomial, distributions, gamma, Multinomial, negative binomial, poisson, statistical distributions

Related Posts

  • Member Training: Logistic Regression for Count and Proportion Data
  • Member Training: A Gentle Introduction to Bootstrapping
  • When Linear Models Don’t Fit Your Data, Now What?
  • Poisson or Negative Binomial? Using Count Model Diagnostics to Select a Model

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