Quantitative Methods Project: Promoting the use of quantitative methods in ethnobiology
General Observations
The Skills & Behaviors listing shows, in general, the developmental path of a typical person who is becoming more and more able to handle quantitative ethnobiology problems.
In a general context, the skill and behavioral levels are defined as the following categories:
Novice: Follows the rules, requires specific rules for specific circumstances, and takes no responsibility other than following the rules.
Advanced Beginner: Expanded view of situations in which the skill is applied, begins to transfer rules to related situations, still makes decisions based on rules, and does not experience personal responsibility.
Competent: Senses that the number of rules is becoming excessive, begins to organize rules by developing principles, starts developing information on the relative importance of particular rules, and begins to experience responsibility relative to decision-making resulting from the application of rules.
Proficient: Problems are solved intuitively based on extensive previous experience, sees the “whole picture,”and applies conscious decision-making by formulatinga plan of action.
Expert: Doesn’t go through the normal processes but intuitively senses what should be done, often without the need for analysis.
Scope of the Quantitative Methods Project
The goal, in general, is to get a person to the Advanced Beginner level.
Skill & Behavioral Levels
Novice
Is familiar with only the most basic statistical concepts, such as "average."
Does not ordinarily use statistics or data visualization.
Makes minimal use of spreadsheet programs, such as Excel, to analyze data.
Has some familiarity in using basic visualizations, such as bar charts and regressions.
Does not fully understand how to use hypotheses relative to statistical tests.
Advanced Beginner
Periodically uses a spreadsheet program to do simple data analysis and visualization.
Creates spreadsheet visualizations by relying on the default values.
Has a basic knowledge of several types of bar charts including how to create and interpret them.
Knows about the "normal" statistical distribution and handles concepts such as the mean and standard deviation.
Understands the concept of hypotheses and their statistical testing.
Is able to do several different kinds of statistical tests by following explicit instructions.
Competent
Uses statistics frequently for a variety of situations.
Understands a variety of statistical distributions.
Creates hypotheses and tests them appropriately.
Employs data visualization as a regular tool.
Adapts data visualization tools to produce high quality results.
Is generally comfortable in analyzing their own data.
Proficient
Handles several statistical packages fluently.
Has sensitivity to subtle aspects of both applying statistics and doing proper interpretations.
Reads statistical literature to keep abreast of recent developments.
Does mash-ups using several data analysis services.
Assists other people in properly analyzing their data.
Expert
Is very facile in using a wide variety of statistical procedures.
Contributes to the statistical literature.