Data Test Facts Flashcards

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1
Q

Explain experimental research style

A
  • one variable is changed (IV) while the others are kept constant
  • Allows researcher to establish a cause-effect relationship between IV and DV
  • consists of control group and an experimental group so results can be compared.
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2
Q

Explain correlation research design style

A
  • measures two variables for a statistical relationship
  • in correlation study, a variable can be any defined numerical value
  • used for quantitative measures
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3
Q

Explain quasi-experiment design.

A
  • quasi-experiments are like true experiments BUT individuals are not randomly allocated into control or experimental groups.
  • this is because they can’t be, the IV is something pre-determined.
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4
Q

Explain case studies design

A
  • in depth study of particular person or group
  • often conducted over long period of time
  • only used in ethically dubious cases or with rare phenomenon
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5
Q

Explain observational research design.

A
  • researcher watching specific behaviours of interest

- it can be done with the participants knowing (overt) or without the participant knowing (covert)

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6
Q

Explain self-report design

A
  • require participants to rate their own behaviours or actions using tools such as questionnaires and surveys.
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7
Q

Explain interviews design

A
  • one on one or small groups can be interviewed by a researcher asking questions.
  • different types of interviews and types of questions to be answered:
  • open questions that require explanation; closed questions that require just one word answers.
  • semi-structured interviews where questions are pre-prepared.
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8
Q

Explain convenience sampling

A
  • non-probability sampling in which a sample is drawn from the part of population that is close to hand
  • no criteria, people just need to be willing to participate.
  • susceptible to sampling bias
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9
Q

Explain repeated measures design

A
  • involves multiple of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods
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10
Q

Explain matched participants/pairs design

A
  • participants are paired with another participant who has a similar trait or characteristic
  • they are then split and allocated to different conditions - attempt to control extraneous variables.
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11
Q

Explain independent groups design.

A
  • different participants are used for each condition in design.
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12
Q

What is a p value

A
  • determines how likely it is that the result occurred by chance alone.
  • the smaller the p value, the more reliable and statistically significant the results are.
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13
Q

What is an alpha level?

A
  • the ideal level that the result occurred by chance alone

- 1% or 5% are common

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14
Q

Explain a t-test and it’s purpose

A
  • test of the null hypothesis
  • 30 people or more
  • assumption of normal distribution.
  • compares difference between between two groups when the dependent variable is either interval or ratio data.
  • unpaired t-test (independent groups) : compares two different sets of subjects
  • paired t-test (within-subjects t-test) : comparisons of same set of subjects exposed to two conditions.
  • PARAMETRIC
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15
Q

What is an alternate hypothesis?

A

The hypothesis which assumes that the data answers the research question.

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16
Q

What is a null hypothesis?

A

The hypothesis which disproves the research question, where the data does not answer the question.

17
Q

Explain a Mann Whitney U test and its purpose.

A
  • test of the null hypothesis
  • does not require assumption of normal distribution.
  • less than 30 participants
  • not as statistically powerful.
  • compares difference when dependent variable is ordinal or continuous.
  • NON-PARAMETRIC
18
Q

What is a confidence interval?

A
  • allows us to estimate the range in which our true population mean falls, given what we know about the population from the sample we’ve observed.
  • always calculated with a given level of certainty (usually 95%), along with standard error or standard deviation.
19
Q

Explain Spearman’s coefficient

A
  • determines how likely it was that the results were found by chance alone (same as p value)
  • non-linear graphs used for
20
Q

What happens to the null hypothesis if the U-crit is bigger than or equal to the U-stat

A

Reject the null hypothesis

21
Q

What happens to the null hypothesis if the U-crit is smaller than the U-stat

A

Fail to reject the null hypothesis