Setting up good Research

Question 1

Population

Answer 1

every individuum of a defined group in the world

Question 2

sample

Answer 2

small subgroup/subpopulation choosen to perform a study on

Question 3

Generalization

Answer 3

the ability to apply findings from a sample to a larger population

Question 4

Random sample

Answer 4

every person of a population has an equal chance of being chosen

Question 5

non-random sample

Answer 5

usually individuals from highly specialized subpopulations

Question 6

probability sample

Answer 6

(most widely used technique)

–> each member of the population has the same chance of being in your sample

Question 7

Representativeness

Answer 7

sample should closely represent the characteristics of the population
–> bbiased samle=not representative

Question 8

Simple Random Sampling (SRS)

Answer 8

randomly selecting a certain number of individuals from the population (e.g. Random digit dialing in a phone survey)

Question 9

Stratified Sampling

Answer 9

Dividing the population into strata, then selecting a random sample from each stratum

Question 10

Proportionate Sampling

Answer 10

Same as stratified sampling but represents the proportions of people in the population in your sample

Question 11

Cluster Sampling

Answer 11

Identify natural occurring groups of participants (clusters) and then randomly select certain clusters and survey all participants within

Question 12

Multistage sampling

Answer 12

Variant of cluster sampling

• > Involves identifying large clusters and randomly selecting from them
• -> Then you randomly select individual elements within those clusters

Question 13

economic sample

Answer 13

a sample that includes enough participants to ensure a valid sample and no more
consider:
1. acceptable error
2. expected magnitude of the population proportions

Question 14

Sampling error

Answer 14

the extend to which the characteristics of the sample differ fromthose of the population

• -> estimated by the margin of error
• most commonly used.95%

Question 15

Laboratory setting

Answer 15

• control over variables (manipulation)

- limits all extraneous variables and isolates the effet of the criterion variable

Question 16

Field setting

Answer 16

You manipulate independent variables and measure a dependent variable, but it is conducted in the real world rather than in a laboratory
–> can easily be generalized

Question 17

Volunteer bias

Answer 17

individuals who volunteer differ from those who do not

–> leads to reduced external validity

Question 18

Volunteerism and motivation

Answer 18

–> volunteerism mediates motivation and my affect inferred causality

Question 19

Internal Validity in a experimental study

Answer 19

Showing that a variation in the independent variable and only in that one, caused the observed variation in the dependent variable

Question 20

Internal Validity in a correlational study

Answer 20

Showing that the changes in value of your criterion variable relate solely to changes in the value of your predictor variable and not other extraneous variables

Question 21

Extraneous variables

Answer 21

variables that can provide an alternative explanation from the findings of a study
–> rival hypothesis

Question 22

Confounding

Answer 22

when the effects of two or more variables cannot be distinguished

Question 23

Threats to internal validity

Answer 23

1. History - events tat occur between obseervations
2. Maturation - performance changes due to age or fatigue
3. Testing/Pretest Sensitisation - Testing prior to the treatment changes how subjects respond in posttreatment testing
4. Instrumentation - Unobserved changes in observer criteria or insturment calibration
5. Statistical regression - regression towards the mean
6. Biased selection of subjects
7. Experimental mortality - differential loss of subjects from the group of a study results in non-equivalent groups

Question 24

Threats to external validity

Answer 24

1. reactive testing - When a pretest affects participants´ reaction to an experimental variable, making that participants responses unrepresentative
2. nteractions between participant selection biases and the independent variable - effects observed might only apply to the participants included in the study, especially if they´re unique to a group
3. Reactive effects of experimental arrangements - the effects of highly artificial experimental situations used in some research and the participant’s knowledge that he or she is a research participant
4. Multiple treatment inference - when participants are exposed to multiple experimental treatments in which exposure to early treatments affects responses to later treatments