Designed Study

An designed study is a planned analysis task that gathers empirical evidence and performs a study evaluation task in order to accept or reject an empirical hypothesis.

• AKA: Research/Scientific Experiment.
• Context:
  • Input: a Research Question (e.g. a hypothesis); and an Experiment Population Sample.
  • output: an Experiment Outcome/Experimental Result.
  • Performance Measure: an Empirical Performance Measure (for Experiment Outcome Performance Result).
  • It can be associated to an Experiment Plan that is produced by an Experiment Design Task.
  • It can range from being an Observational Study (such as quasi-experimental study) to being an Interventional Study (with subject-assignment and post-test measures).
  • It can range from being a Categorical Outcome Study to being an Ordinal Outcome Study to being a Continuous Outcome Study.
  • It can range from being a Envisioned Designed Study to being an Active Designed Study to being a Inactive Designed Study (such as a concluded designed study).
  • It can support a Research Task (that investigates a research question).
  • It can be a Part Of an Empirical Research Task.
  • It can be used to debunk Received Wisdom.
  • …
• Example(s):
  • Observational Studies, such as: Piazzi's Study of Ceres in 1801.
  • Interventional Experiments, such as: Lind's Scurvy Cure Experiment of 1747.
  • Field Experiments, such as: ...
  • an Empirical Algorithm Performance Evaluation Task (that would use a benchmark elgorithm).
  • a Designed Clinical Study.
  • …
• Counter-Example(s):
  • a Stochastic Process.
  • an Adhoc Experiment, such as an Informal Survey.
• See: Analytical Study, Theoretical Study, Experimental Analysis Task.

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References

2014?

• Jeff Bezos.
  • “If you already know it's going to work, it's not an experiment, and only through experimentation can you get real invention. The most important inventions come from trial and error with lots of failure, and the failure is critical, and it's also embarrassing.”
  • "If you double the number of experiments you do per year, you're going to double your inventiveness."

2013

• http://en.wikipedia.org/wiki/Design_of_experiments
  • In general usage, design of experiments (DOE) or experimental design is the design of any information-gathering exercises where variation is present, whether under the full control of the experimenter or not. However, in statistics, these terms are usually used for controlled experiments. Formal planned experimentation is often used in evaluating physical objects, chemical formulations, structures, components, and materials. Other types of study, and their design, are discussed in the articles on computer experiments, opinion polls and statistical surveys (which are types of observational study), natural experiments and quasi-experiments (for example, quasi-experimental design). See Experiment for the distinction between these types of experiments or studies.

    In the design of experiments, the experimenter is often interested in the effect of some process or intervention (the "treatment") on some objects (the “experimental units"), which may be people, parts of people, groups of people, plants, animals, etc. Design of experiments is thus a discipline that has very broad application across all the natural and social sciences and engineering.

2013

• http://en.wikipedia.org/wiki/Empirical_research
  • Empirical research is a way of gaining knowledge by means of direct and indirect observation or experience. Empirical evidence (the record of one's direct observations or experiences) can be analyzed quantitatively or qualitatively. Through quantifying the evidence or making sense of it in qualitative form, a researcher can answer empirical questions, which should be clearly defined and answerable with the evidence collected (usually called data). Research design varies by field and by the question being investigated. Many researchers combine qualitative and quantitative forms of analysis to better answer questions which cannot be studied in laboratory settings, particularly in the social sciences and in education.

    In some fields, quantitative research may begin with a research question (e.g., "Does listening to vocal music during the learning of a word list have an effect on later memory for these words?") which is tested through experimentation in a lab. Usually, a researcher has a certain theory regarding the topic under investigation. Based on this theory some statements, or hypotheses, will be proposed (e.g., "Listening to vocal music has a negative effect on learning a word list."). From these hypotheses predictions about specific events are derived (e.g., "People who study a word list while listening to vocal music will remember fewer words on a later memory test than people who study a word list in silence."). These predictions can then be tested with a suitable experiment. Depending on the outcomes of the experiment, the theory on which the hypotheses and predictions were based will be supported or not.

2012

• (Wikipedia, 2012) ⇒ http://en.wikipedia.org/wiki/Experiment
  • An experiment is a methodical trial and error procedure carried out with the goal of verifying, falsifying, or establishing the validity of a hypothesis. Experiments vary greatly in their goal and scale, but always rely on repeatable procedure and logical analysis of the results. A child may carry out basic experiments to understand the nature of gravity, while teams of scientists may take years of systematic investigation to advance the understanding of a phenomenon.

    An experiment is a method of testing - with the goal of explaining - the nature of reality. Experiments can vary from personal and informal (e.g. tasting a range of chocolates to find a favourite), to highly controlled (e.g. tests requiring complex apparatus overseen by many scientists hoping to discover information about subatomic particles).

    In the design of comparative experiments, two or more "treatments" are applied to estimate the difference between the mean responses for the treatments. For example, an experiment on baking bread could estimate the difference in the responses associated with quantitative variables, such as the ratio of water to flour, and with qualitative variables, such as strains of yeast. Experimentation is the step in the scientific method that helps people decide between two or more competing explanations – or hypotheses. These hypotheses suggest reasons to explain a phenomenon, or predict the results of an action. An example might be the hypothesis that "if I release this ball, it will fall to the floor": this suggestion can then be tested by carrying out the experiment of letting go of the ball, and observing the results. Formally, a hypothesis is compared against its opposite or null hypothesis ("if I release this ball, it will not fall to the floor"). The null hypothesis is that there is no explanation or predictive power of the phenomenon through the reasoning that is being investigated. Once hypotheses are defined, an experiment can be carried out - and the results analysed - in order to confirm, refute, or define the accuracy of the hypotheses.

2009

• (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=experiment
  • S: (n) experiment, experimentation (the act of conducting a controlled test or investigation)
  • S: (n) experiment, experimentation (the testing of an idea) "it was an experiment in living"; "not all experimentation is done in laboratories"
  • S: (n) experiment (a venture at something new or different) "as an experiment he decided to grow a beard"
  • S: (v) experiment (to conduct a test or investigation) "We are experimenting with the new drug in order to fight this disease"
  • S: (v) experiment, try out (try something new, as in order to gain experience) "Students experiment sexually"; "The composer experimented with a new style"

1998

• (Saint-Germain, 1998) ⇒ Michelle A. Saint-Germain. (1998). “Experimental Designs for Research." PPA 696 RESEARCH METHODS
  • QUOTE: establish whether two variables are causally related, that is, whether a change in the independent variable X results in a change in the dependent variable Y, you must establish:
    1. ) time order --The cause must have occurred before the effect;
    2. ) co-variation (statistical association) -- Changes in the value of the independent variable must be accompanied by changes in the value of the dependent variable;
    3. ) rationale -- There must be a logical and compelling explanation for why these two variables are related;
    4. ) non-spuriousness -- It must be established that the independent variable X, and only X, was the cause of changes in the dependent variable Y; rival explanations must be ruled out.
  • To establish causality, one must use an experimental or quasi-experimental design. Note that it is never possible to prove causality, but only to show to what degree it is probable.

1990

• (Brown & Melamed, 1990) ⇒ Steven R. Brown, and Lawrence E. Melamed. (1990). “Experimental Design and Analysis." SAGE Publications, Inc . ISBN:9780803938540
  • QUOTE:experimentation can be viewed as an extension of inquisitiveness, and consequently is as old as curiosity itself. There is evidence that it was beginning to take root as an organized procedure as early as the thirteenth century when the received wisdom of the Greeks was being questioned. In a more formal sense, however, the experimental method received its greatest impetus from the scientific advances of the sixteenth and seventeenth centuries, and it was because of its success that Sir Isaac Newton could confidently state that "the qualities of bodies are only known to us by experiments." By the twentieth century, "classical" experimentation - the practice of holding everything constant except the one variable under consideration-was widely accepted in the sciences, but "modern" experimentation dates from the publication in 1935 of Sir Ronald A. Fisher's "The Design of Experiments."

1960

• (Fisher, 1960) ⇒ R. A. Fisher. (1960).
  • QUOTE: " … [experimentation is] experience carefully planned in advance … " (p. 8),

1935

• (Fisher, 1960) ⇒ R. A. Fisher. (1935). “The Design of Experiments."

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