Experimental Design (Labs 7 + 8) Flashcards

1
Q

What are the components of good experimental design? (6)

A

1) Refutable Hypothesis (testable)
2) Well Controlled
3) Reproducible
4) Minimization of Bias
5) Representative
6) Applicable Statistics

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2
Q

How many groups (at minimum) must an experiment have (in the context of this course)?

A

TWO
1) Experimental Group
2) Control Group

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3
Q

Control vs Experimental Groups

A

Control group receives exactly the same treatment as the experimental group, EXCEPT for the variable that is being tested!

Control = NO treatment
Experimental = Treatment

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4
Q

What is a control experiment?

A

An experiment that has a “known” outcome

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5
Q

Positive vs Negative Control
(+ what are the purposes of each)

A

Positive control = Experiment that is expected to produce a KNOWN EFFECT
–> Used to make sure that your procedure is working properly

Negative Control = Experiment that is expected to produce NO EFFECT
–> Used to identify confounding variables

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6
Q

Null Hypothesis

A

The hypothesis in which NO relationship exists between two sets of data or variables being analyzed

–> Most statistical tests assume the null hypothesis to be true: operates under the assumption that there is no significant difference or association between groups unless the data strongly suggests otherwise

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7
Q

In what type of experiment are null hypotheses used?

A

Any experiment that is statistically testing for a significant difference or relationship between variables

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8
Q

Alternate Hypothesis

A

Implies that there IS a relationship between two sets of data/variables being analyzed

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9
Q

What is a p-value?

A

The probability (likelihood) of a result occurring by chance

The lower the p-value, the less likely the result occurred due to random chance (and was likely due to the treatment)

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10
Q

At What P Value Would a Scientist Reject the Null Hypothesis?

A

P < 0.05 (Probability of effect occurring due to chance < 5%)

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11
Q

Qualitative Data

A

Descriptive information that cannot be quantified by numbers; data sorted by category, not by number

–> Can consist of audio, images, symbols, or text

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12
Q

Quantitative Data

A

A type of data that can be expressed in numerical values

–> Countable and can therefore undergo statistical data analysis and can be plotted

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13
Q

What are the two types of qualitative data?

A

1) Nominal
2) Ordinal

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14
Q

What are the two types of quantitative data?

A

1) Discrete
2) Continuous

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15
Q

Nominal Data

A

Qualitative data that categorizes variables into distinct groups with no inherent order or ranking (essentially acting as labels or names without any numerical value)

Ex: Gender

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16
Q

Ordinal Data

A

Qualitative data that groups variables into ordered categories

–> The categories have a natural order or rank based on some hierarchal scale (Ex: high to low) but there is no clearly defined interval between the categories!

17
Q

Discrete Data

A

Countable data that has FINITE values (integers/whole #s)

–> Subdivision is not possible! (no fractions or decimals!)

Ex: # of people in a room (you can’t split a person in half)

18
Q

Continuous Data

A

Data that can take on any value within a specific range (can include fractions and decimals!)

–> Typically refers to measured data using a scale of some kind

Ex: Height of a person