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Statistical Consulting

The Wisdom of Asking Silly Statistics Questions

by Karen Grace-Martin 2 Comments

I’ve written about this before–there is just something about statistics that makes people feel…well, not so smart.

This makes people v-e-r-y reluctant to ask questions.

This fact really struck me years and years ago.  Hit me hard.

[Read more…] about The Wisdom of Asking Silly Statistics Questions

Tagged With: Statistical Consultant, Statistical Consulting, statistical learning, statistical questions, statistics

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5 Practical Issues to Consider in Choosing a Statistical Analysis

by Karen Grace-Martin 1 Comment

There are 4 questions you must answer to choose an appropriate statistical analysis.

1. What is your Research Question?
2. What is the scale of measurement of the variables used to answer the research question?
3. What is the Design? (between subjects, within subjects, etc.)
4. Are there any data issues? (missing, censored, truncated, etc.)

If you have not already, read about these in more detail.

[Read more…] about 5 Practical Issues to Consider in Choosing a Statistical Analysis

Tagged With: Assumptions, choosing statistical analysis, data, Statistical Consulting

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Statistical Consulting 101: 4 Questions you Need to Answer to Choose a Statistical Method

by Karen Grace-Martin 1 Comment

One of the most common situations in which researchers get stuck with statistics is choosing which statistical methodology is appropriate to analyze their data. If you start by asking the following four questions, you will be able to narrow things down considerably.

Even if you don’t know the implications of your answers, answering these questions will clarify issues for you. It will help you decide what information to seek, and it will make any conversations you have with statistical advisors more efficient and useful.

1. What is your research question? [Read more…] about Statistical Consulting 101: 4 Questions you Need to Answer to Choose a Statistical Method

Tagged With: Research Question, Scales of Measurement, Statistical Consulting, Study design

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Poisson and Negative Binomial Regression Models for Count Data

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