quantitative research Flashcards

Question

credibility in experimenyal studies (table)

Answer 1

Internal validity: to what extent is the DV inuenced by the IV and not some other variable? Controlling confounding variables: eliminating or keeping constant in all conditions

Answer 2

Credibility = trustworthiness. To what extent do the ndings reect the reality? -Triangulation -Establishing a rapport -Iterative questioning -Reexivity -Credibility checks -Thick descriptions

Answer 3

No special term used: “validity” and “credibility” can be used interchangeably Credibility is high if no bias occurred

Answer 4

Threats to internal validity: – Selection – History – Maturation – Testing effect – Instrumentation – Regression to the mean – Experimental mortality – Experimenter bias – Demand characteristics

Answer 5

On the level of measurement of variables: depends on the method of measurement On the level of interpretation of ndings: – Curvilinear relationships – The third variable problem – Spurious correlations

Answer 6

Participant bias: – Acquiescence – Social desirability – Dominant respondent – Sensitivity Researcher bias: – Conrmation bias – Leading questions bias – Question order bias – Sampling bias – Biased reporting

Answer 7

Variables that can potentially distort the relationship between the IV and the DV are called confounding variables. They contribute to bias. These variables need to be controlled, either by eliminating them or keeping them constant in all groups of participants so that they do not affect the comparison.

Answer 8

The target population is the group of people to which the ndings of the study are expected to be generalized. The sample is the group of people taking part in the experiment itself.

Answer 9

- This is the ideal approach to make the sample representative. - In random sampling every member of the target population has an equal chance of becoming part of the sample. - With a sufcient sample size this means that you take into account all possible essential characteristics of the target population, even the ones you never suspected to play a role. - Arguably, a random sample of sufcient size is a good representation of a population, making the results easily generalizable. - However, random sampling is not always possible for practical reasons.

Answer 10

A sample is said to be representative of the target population if it reects all its essential characteristics.

Answer 11

- theory-driven. First you decide the essential characteristics the sample has to reect. - Then you study the distribution of these characteristics in the target population - Then you recruit your participants in a way that keeps the same proportions in the sample as is observed in the population randomly or use other approaches - it ensures that theory-dened essential characteristics of the population are fairly and equally represented in the sample. - This may be the ideal choice when you are certain about essential participant characteristics and when available sample sizes are not large.

Answer 12

- For this technique you recruit participants that are more easily available. - There could be several reasons for choosing convenience sampling. - First, it is the technique of choice when nancial resources and time are limited. - Second, there could be reasons to believe that people are not that different in terms of the phenomenon under study. - Finally, convenience sampling is useful when wide generalization of ndings is not the primary goal of your research,

Answer 13

- This refers to recruiting volunteers. - The strength of self- selected sampling is that it is a quick and relatively easy way to recruit individuals while at the same time having wide coverage - The most essential limitation, again, is representativeness. - People who volunteer to take part in experiments may be more motivated than the general population, or they may be looking for the incentives

Answer 14

-involves random allocation of participants into groups and a comparison between these groups. - In its simplest form, you randomly allocate participants from your sample into the experimental group and the control group. - Then you manipulate the experimental conditions so that they are the same in the two groups except for the independent variable. - After the manipulation you compare the dependent variable in the two groups. - The rationale behind random group allocation is that all potential confounding variables cancel each other out. - If the groups are not equivalent at the start of the experiment, you will be comparing apples to oranges. - Conversely, when the group sizes are sufciently large and allocation is completely random, chances are that groups will be equivalent—the larger the sample, the higher the chance.

Answer 15

similar to independent measures. The only difference is that instead of completely random allocation, researchers use matching to form the groups. The variable that is controlled is called the matching variable. Matched pairs designs are preferred when: ● the researcher nds it particularly important that the groups are equivalent in a specic variable ● the sample size is not large, therefore there is a chance that random allocation into groups will not be sufcient to ensure group equivalence.

Answer 16

- Repeated measures design is used when the goal is to compare conditions rather than groups of participants. - The same group of participants is exposed to two (or more) conditions, and the conditions are compared. - The problem with repeated measures designs is that they are vulnerable to order effects: - resultsmay be different depending on which condition comes rst - Order effects may appear due to various reasons, such as the following. ● Practise: participants practise, improve their on-task concentration and become more comfortable with the experimental task during the rst trial. Their performance in the second trial increases. ● Fatigue: participants get tired during the rst trial, and their concentration decreases. Their performance in the second trial decreases. - An advantage of repeated measures designs is that people are essentially compared to themselves, which overcomes the inuence of participant variability - Another advantage following from this is that smaller sample sizes are required.

Answer 17

To overcome order effects researchers use counterbalancing. Counterbalancing involves using other groups of participants where the order of the conditions is reversed.

Answer 18

Construct validity characterizes the quality of operationalizations.Moving from an operationalization to a construct is always a bit of a leap. Construct validity of an experiment is high if this leap is justied and if the operationalization provides sufcient coverage of the construct.

Answer 19

Internal validity characterizes the methodological quality of the experiment. Internal validity is high when confounding variables have been controlled and we are quite certain that it was the change in the IV (not something else) that caused the change in the DV. In other words, internal validity links directly to bias: the less bias, the higher the internal validity of the experiment.

Answer 20

Population validity refers to the extent to which ndings can be generalized from the sample to the target population. Population validity is high when the sample is representative of the target population and an appropriate sampling technique is used.

Answer 21

Ecological validity refers to the extent to which ndings can be generalized from the experiment to other settings or situations. It links to the articiality of experimental conditions. In highly controlled laboratory experiments subjects often nd themselves in situations that do not resemble their daily life.

Answer 22

External validity characterizes generalizability of ndings in the experiment. There are two types of external validity: population validity and ecological validity.

Answer 23

-Occurs if the groups are not equivalently controlled for variable besides the independent variable thats supposed to change at the start of the experiment -Therefore, inferences cannot be made about the influence of the IV on the DV -Usually happens because case group allocations were not truly randomised

Answer 24

-The outside events participants experience during the course of the experiment -May affect the internal validity as the dependent variable may change as a result of the event -The presence of confounding variables may be controlled, in an experiment by either controlling or eliminating them

Answer 25

-the natural developmental processes participants go through over the course of the experiment -May affect internal validity as there is no telling whether the IV affected the final results of natural growth and development -May be counteracted by using a control group (a group that does not experience the enforcement of the IV and is the same in every other respect)

Answer 26

-The first measurement of the dependent variable may affect the second and so on and so forth -Thus, it is important to have a control group to discern what results are from the testing effect and what results are from the changing the IV

Answer 27

-Occurs when the instrument measuring the DV results changes slightly between measurements -Especially poignant in psychology as most instruemnts of measurement are human observers -Can be avoided by setting standardized measurement conditions accross all comparison groups and observers

Answer 28

-Refers to the fact that some participants drop out of the experimeent before it has concluded, which may cause problems if the dropouts are not random, which would lead to a lack of equivalence between controlled and experimental groups -There is no advised way to combat mortality, except creating an environment that does not prompt dropping out

Answer 29

-more intriguing source of bias that increasingly prevalent in experiments where initial DV score is an extremely low or high -As extremes have a statistical tendency to average out as the trials continue or as trial repeat. This is true for any trial in which luck in involved -A countermeasure one may take is a control group with the same baseline starting point and measurements of the same point as well, however, without intervention -it it very common to infer causation when regression to the mean is actually present

Answer 30

-This refers to when particpants become aware of the aim of the experiment and (subconciously) chang etheir behabiour according to fit their interpretation -A viable countermeasure in many cases could be deception, in which you make it difficult for particpants to discern the aim of the experiment (but this may raise ethical concerns) -Another countermeasure may be a post-exxperimental questionnaire to find out the degree of involvement of deman characteristics in the results -The threat of demand characteristics increases in repeated measures designed experiments

Answer 31

-Occurs in a situation in which the researcher unintentionally exerts an influence over the results of the study -A countermeasure for experimenter bias is double blind designs in which information which could induce subconcious bias is withhels from not only participants but also researchers

Answer 32

- Quasi-experiments are different from “true” experiments in that the allocation into groups is not done randomly. - Instead some pre-existing inter-group difference is used. - - The major limitation of a quasi-experimental design is that cause-and-effect inferences cannot be made. - This is because we cannot be sure of the equivalence of comparison groups at the start of the study - pre-existing differences in one variable may be accompanied by - In the way they are designed (supercially) quasi experiments resemble “true” experiments, but in terms of the possible inferences (essentially) they are more like correlational studies.

Answer 33

- Field experiments are conducted in a real- life setting. - The researcher manipulates the IV, but since participants are in their natural setting many extraneous variables cannot be controlled. - The strength of eld experiments is higher ecological validity as compared to experiments in a laboratory. - The limitation is less control over potentially confounding variables so there is lower internal validity.

Answer 34

- Natural experiments, just like eld experiments, are conducted in participants’ natural environment, but here the researcher has no control over the IV—the IV occurred naturally. - Ecological validity in natural experiments is an advantage and internal validity is a disadvantage owing to there being less control over confounding variables. - Another advantage of natural experiments is that they can be used when it is unethical to manipulate the IV -all natural experiments are quasi experiments as the researchers do not manipulate any IV's

Answer 35

A correlation is a measure of linear relationship between two variables. Graphically a correlation is a straight line that best approximates this “cloud” in the scatter plot.

Answer 36

A positive correlation demonstrates the tendency for one variable to increase as the other variable increases. A negative correlation demonstrates the inverse tendency: when one variable increases the other variable decreases. The steeper the line, the stronger the relationship.

Answer 37

The absolute value of the correlation coefcient (the number from −1 to 1) is called the effect size.

Answer 38

- Statistical signicance shows the likelihood that a correlation of this size has been obtained by chance. - It depends on the sample size: with small samples you cannot be sure that an obtained correlation, even if it is relatively large, has not been obtained due to random chance. - With large samples correlation estimates are more reliable and you can be more condent that the correlation is not a product of random chance but a genuine reection of a relationship between the two variables in the population. - The probability that a correlation has been obtained due to random chance can be estimated.

Answer 39

- correlations cannot be interpreted in terms of causation -the third variable problem:There is always a possibility that a third variable exists that correlates both with X and Y and explains the correlation between them. -curvilinear relationships: -spurious correlations

Answer 40

- When a research study involves calculating multiple correlations between multiple variables, there is a possibility that some of the statistically signicant correlations would be the result of random chance. - When we calculate 100 correlations and only pick the ones that turned out to be signicant, this increases the chance that we have picked spurious correlations.

Answer 41

- Sometimes variables are linked non-linearly. - However, this relationship can only be captured by looking at the graph. - Since correlation coefcients are linear, the best they could do is to nd a straight line that ts best to the scatter plot. -Psychological reality is complex and there are a lot of potentially curvilinear relationships between variables, but correlational methods reduce these relationships to linear, easily quantiable patterns.

Answer 42

Bias in correlational research can occur on the level of variable measurement and on the level of interpretation of ndings. On the level of measurement of variables, various biases may occur and they are not specic to correlational research.