Unit 1 List 2 Experimental Design Flashcards

(18 cards)

1
Q

Claim

A

To assure or take something for granted

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2
Q

Constant

A

A constant is the part that does not change during the experiment.

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3
Q

Evidence

A

conscious, explicit and judicious use of valid and available data from scientific research

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4
Q

Experimental bias

A

defect in the design of a scientific research study or clinical trial, or in the method used to collect or interpret the information

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5
Q

Experimental control

A

scientific test done under controlled conditions

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6
Q

Experimental procedure

A

set of characteristics that govern the realization of a certain random phenomenon

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7
Q

Hypothesis

A

makes a prediction about the relationship between two variables, and only two variables

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8
Q

Manipulated variable

A

makes a prediction about the relationship between two variables, and only two variables

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9
Q

Qualitative data

A

Data expressed in the form of words or texts that help to understand certain actions and attitudes of respondents that are not quantifiable

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10
Q

Quantitative data

A

any quantifiable information that can be used to perform mathematical calculations and statistical analysis

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11
Q

Reason

A

It is the one that contains the regulatory principles of the systematic unit in its highest degree of internal coherence, in such a way that understanding approaches knowledge.

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12
Q

Responding variable

A

outcome measured within a trial that may be influenced by other factors

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13
Q

Scientific method

A

The scientific method is a way of testing hypotheses.

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14
Q

Scientific model

A

It is a bridge to connect a scientific theory with a phenomenon.

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15
Q

Scientific question

A

question whose answer is clearly read in the conclusions and from which it is easy to deduce what the researchers want to know.

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16
Q

Scientific theory

A

set of theoretical statements formulated syntactically (axioms, theorems and laws) together with their interpretation via correspondence statements`

17
Q

Trends in data

A

new and evolving methodologies, technologies and practices that are shaping the future of data analysis and interpretation.