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Research & Experiments

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The Scientific Method

graphical flowchart of the scientific method from: http://whyfiles.larc.nasa.gov/text/educators/tools/pbl/scientific_method.html

NASA SCIence Files


Deductive & Inductive Reasoning


   Deduction is one form of finding answers to problems.  Deduction is in the form of an argument that must be both true and valid to be correct.  The premises must be true and the conclusion that follows the premise must be valid.  A deduction is valid only if the conclusion cannot be proven false.  Deduction can take the form of an if/then statement, or several premises, which are true statements, followed by a conclusion.

o   Example:

  Children misbehave when they are bored. (premise 1)

  Children are usually bored in grocery stores. (premise 2)

  Children love cookies. (premise 3)

  Parents who stop by the in-store bakery first to get their child a cookie normally don’t experience misbehaving children while shopping. (conclusion)




   Induction is different in that the conclusion is drawn from a particular fact or piece of evidence.  The conclusion will explain the facts; like investigating a crime scene and putting the pieces of evidence together to form answers, keeping in mind the conclusion is your hypothesis.

o   Example:

  Chaz’s territory is #1 in the entire region because he has great communication and feedback with his stores.

  Kristin looks 15 years younger than her peers because she uses sunscreen.



Quantitative and Qualitative Research



Types of Data


Nominal Lowest Level   Nonpragmatic


  Tall to short Nonpragmatic
Interval   work with statistics  %, no absolute 0 Pragmatic
Ratio Highest Level most useful data, includes absolute 0, raw score on test Pragmatic


Central Tendency





Average deviation from the mean



Types of Research Designs


Experimental (& Quasi-Experimental)






Grounded Theory






Mixed Method



A Few Notes on Survey Research

There are several factors that limit a survey researcher’s ability to draw valid inference from a sample to a population. Below is a  list of these factors and ways in which a researcher might reduce such errors.

First, let's define terms...

Inference: An assertion made on the basis of something else observed or taken as knowledge; used in deductive (known in advance) and inductive (made more probable based on prior observations/experiments) arguments.


bulletTo reduce coverage error, have a good sampling frame list on which to select individuals. 
bulletTo reduce sampling error, select as large a sample from the population as possible.
bulletTo reduce measurement error, use a good instrument with clear, unambiguous questions and response options.  This encourages response & correct answers.
bulletTo reduce non-response error, use rigorous administration procedures to achieve as large a return rate as possible.


Graphic Organizers

Reptile Research


Research Briefs

Math Used in Science


NASA Space Research


PathFinder Science



Writing in Science



Experiments utilize different types of technology and equipment in science, but all experiments share common goals:


understand problems


develop hypotheses


design and implement controlled experiments


identify independent and dependent variables


analyze data


draw conclusions


think analytically


communicate results (using the proper data tables and graphs)


Pre-experiment   True experiment   Quasi-experiment

      Weak in scientific measurement

       Fails to adequately control threat on internal validity   (Cooper, 2006).



Randomly assigns participants to different conditions.

         Experimental group will get experimental treatment

         Control group does not get treatment, it remains untouched

         Most threats to internal validity do not arise

         The researcher randomly assigns participants to different conditions of the experimental variable



Design looks like a pre-test/post-test design but it lacks the random assignment of the control groups.

  No random assignment

  Uses existing or intact group for study

  More threats to internal validity than true experiments

  No random assignment of participants or groups

  This approach introduces more threats to  internal validity:












Threats To Validity

bulletMaturation   (Cooper, 2006) has to do with the passage of time and occurs when the subjects being studied have no specificity to any particular event within the experiment.
bulletHistory – causes confusion within the relationship being studied due to a particular event that occurs during the experiment.
bulletTesting or Pretest gives unfair advantage for post test answers in experiment.
bulletPresence of confusing variables if the researcher uses too many variables at once and cannot determine which variable affected the experiment.
bulletHawthorne Effect  (Clark, 1999) could alter the effect of the experiment if the subject(s) know they are being watched or studied.
bullet Experimenter Effect –experiment only works with current experimenter or researcher.  With another person performing the experiment the effect is not the same. No repeatability.



Slide from Mrs. King's Education Research PPT 2003




Miami Museum of Science

Science Exploritorium


More Experiments

Science Projects

Dragonfly TV

Newtonian Physics

Scientific Method

Education Excellence

Noggin- Bill Nye

Static Electricity Generator

Fun Science


High School Projects

Reeko's Mad Scientist

Try Science

Home Experiments


Types of Sources

Interactive Experiments

Saturday Scientist

Van de Graaff Generator
Kitchen Scientist

Science Club

You Try It

Science Explorer

Virtual Lab




Clark, D. (1999). Hawthorne effect. Retrieved May 22, 2007, from The Hawthorne Effect: http://www.nwlink.com/~donclark/hrd/history/hawthorne.html

Cooper, et al. (2006). In Business research methods (p.283). New York: McGraw-Hill/Irwin.

Last modified: March 27, 2013