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STEP OR STAGE #6 of the Scientific Method

EVALUATE THE EVIDENCE


Using the Scientific Method

By now you should have a list of tentative solutions that are candidates for your educated guess or hypothesis.

This is also the step or stage for experimenting and testing. The final choice is often called your working hypothesis and will be your. Step of Stage #7.


Applying the Scientific Method

Starting guides to review before working on each Step or Stage:
  • Problem: Should it be redefined or reframed?
  • Goals and planning: Any changes? Any new leads or clues? Planning ahead?
  • Goal-referencing approach: Where you started, are at now, and still need to go.
  • Looking back: Have you been using the right attributes, methods, strategies, technologies, plus curious observation? Have you consulted your advisor? Have you had a team meeting? Are you keeping your log up-to-date? Being on the right path is important!
  • Are you using innovation, creativity, watching for surprises? Are you alert to clues and leads?
  • Are you putting thoughts and ideas into writing? Using all available resources?

Evaluating Your Tentative Hypotheses

  • If data on any of these scientific method hypotheses is insufficient, gather additional information.
  • Check against any list of criteria, formulas, and routines you have established.
  • It may be helpful to read the information on .Ingredient #7 to familiarize yourself with the characteristics and traits your working hypothesis must have.
Also, read Step or Stage #8 to alert you as to how it will have to be challenged.

Using the Scientific Method

Tests, Experiments, Strategies, Techniques
& Other Methods of Evaluating Evidence

Here is a checklist for these methods:
Measuring Logical reasoning Mathematical solution
Surveys Collaborators Independent lab test
Interviews Expert opinions Controlled experiments
Modeling Concepts correct? Dis-confirming tests
Graphs Improvisation Data base reliable?

Sampling Disqualifying Consider consequences
Speculation. Make predictions Challenge assumptions
Simulations Statistical analysis Design special instruments
"Live It" Computer testing "Anything goes" theory
Visualizing Consult literature Need to ripen more?


Scientific Method Chart or Matrix

Chart Your Solutions to Weigh the Evidence

Using a chart you will be more careful in making your choice or conclusion. Criteria can be graded by as many facets, characteristics or angles as you desire. You can have individual charts or a joint one. Tailor headings to fit your problem.

Possible Comparison Chart

Tentative Choices Test Results Suitability Feasibility Acceptability
  #1 #2 #1 #2 #1 #2 #1 #2
Solution A Against For 30% Okay 60% Okay 50% 90%
Solution B For Against 50% No 80% No 90% 20%



Scientific Method Variables

Evaluate Carefully, but Remember - Perfection Is Not Always Possible.

Variables such as time, money emergencies, importance, practicability, and constraints on human thinking often mean we can't be thorough enough, even though we would like to be.

Bounded Rationality

Thus we must often settle for "good enough." similar descriptions are tolerance of ambiguity, aspiration level, most optimum not needed, satisfactory versus optional standards, adequate for problem, risk within reason, bounded rationality.

Using the Scientific Method - General Principles

The general principles in considering all your efforts:

Accept uncertainty of solution Perfectionism is not always affordable
"Truth" may not exist Rate: Good--Better--Good enough
Consider community "standards" Precision - important in science
Waste no time on little differences No excuse for sloppy work
No single best solution may exist No better action to take

Using the Scientific Method

A good base of actual experiences or reading of other people's experiences will be of great value in making a quick decision on matters of minor importance, but remember if you make decisions on wrong "facts," what follows are wrong decisions.

Learn to evaluate as - good, better, good enough, or not good enough - and search for further data keeping in mind costs vs. benefits.