Data Test Facts

Question 1

Explain experimental research style

Answer 1

• 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.

Question 2

Explain correlation research design style

Answer 2

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

Question 3

Explain quasi-experiment design.

Answer 3

• 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.

Question 4

Explain case studies design

Answer 4

• 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

Question 5

Explain observational research design.

Answer 5

• researcher watching specific behaviours of interest

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

Question 6

Explain self-report design

Answer 6

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

Question 7

Explain interviews design

Answer 7

• 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.

Question 8

Explain convenience sampling

Answer 8

• 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

Question 9

Explain repeated measures design

Answer 9

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

Question 10

Explain matched participants/pairs design

Answer 10

• 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.

Question 11

Explain independent groups design.

Answer 11

• different participants are used for each condition in design.

Question 12

What is a p value

Answer 12

• 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.

Question 13

What is an alpha level?

Answer 13

• the ideal level that the result occurred by chance alone

- 1% or 5% are common

Question 14

Explain a t-test and it’s purpose

Answer 14

• 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

Question 15

What is an alternate hypothesis?

Answer 15

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

Question 16

What is a null hypothesis?

Answer 16

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

Question 17

Explain a Mann Whitney U test and its purpose.

Answer 17

• 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

Question 18

What is a confidence interval?

Answer 18

• 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.

Question 19

Explain Spearman’s coefficient

Answer 19

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

Question 20

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

Answer 20

Reject the null hypothesis

Question 21

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

Answer 21

Fail to reject the null hypothesis