Research Methods-Experiments

Question 1

Define Laboratory Experiment

Answer 1

Experiments in a lab where variables can be controlled.

Question 2

List advantages of laboratory experiments

Answer 2

Easily controlled.
High in validity.
Reliable as they can be easily replicated

Question 3

List disadvantages of laboratory experiments

Answer 3

Low in ecological validity (doesn’t replicate real life).

Demand Characteristics mean they could work out the study and behave how you want them to.

Question 4

Define Field Experiment

Answer 4

Experiments done in natural environment e.g. classroom

Question 5

List advantages of field experiments

Answer 5

High in ecological validity.
Natural environment comparable to real life.
No demand characteristics if participants unaware increasing the validity.

Question 6

List disadvantages of field experiments

Answer 6

Researcher cannot control all factors e.g. time and weather.

Raises ethical issues if participants are unaware.

Question 7

Define Naturalistic (Quasi) Experiments

Answer 7

Can be a natural lab experiment or natural field experiment.

Question 8

List advantages of naturalistic experiments

Answer 8

Allows us to access groups that would otherwise be unethical or impossible to test.

Question 9

List disadvantages of naturalistic experiments

Answer 9

Can be difficult to get participants.

Question 10

Define independent variable

Answer 10

The variable that the researcher manipulates.

Question 11

Define dependent variable

Answer 11

A particular behaviour that is dependent on the way the experimenter manipulates the independent variable.

Question 12

Define experimental (alternate) hypothesis

Answer 12

Tests the cause of independent variable on the effect of dependent variable

Question 13

Define directional hypothesis (1 tailed hypothesis)

Answer 13

Predicts the direction in which results are expected to occur.

Question 14

Define non-directional hypothesis (2 tailed hypothesis)

Answer 14

Does not predict the expected direction of outcome but will state that there is some kind of difference between the two events

Question 15

Define null hypothesis

Answer 15

Predicts that there will be no differences between the two variables

Question 16

Define extraneous variables

Answer 16

Things that affect the behaviour of participants e.g. environmental conditions like light, noise and heat.

Question 17

Define confounding variables

Answer 17

When the extraneous variables align themselves with the experimenter’s manipulation of the independent variable. It confounds the experimenters attempts to interpret the findings of the experiment in the intended way.

Question 18

Define independent measures

Answer 18

Involves using different participants in each of the experimental designs. By comparing the performance of participants between conditions, you can establish whether or not the independent variable affects the participants’ behaviour.

Question 19

List advantages of independent measures design

Answer 19

No problems caused by order affects (where learning, boredom or fatigue can influence the second condition).

Question 20

List disadvantages of independent measure design

Answer 20

Differences in performance between two groups may be due to individual differences rather than manipulation of independent variable.

Question 21

Define repeated measures

Answer 21

Comparing the performance of people in one condition with their own performance in another condition.

Question 22

List advantages of repeated measures design

Answer 22

Individual differences are removed.

Question 23

List disadvantages of repeated measures design

Answer 23

There are order effects.
Participants may perform better in the second condition because of the practice they will have gained during the previous condition (positive order effect). They may perform worse as a result of boredom (negative order effects).

Question 24

Define matched pairs

Answer 24

Matching participants in one of the conditions to another one of the participants in the second condition according to variables that are considered to be relevant to experimental conditions. E.g. may be matched for age, gender and intelligence.

Question 25

List advantages of matched pairs design

Answer 25

No individual differences or order effects

Question 26

List disadvantages of matched pairs design

Answer 26

Difficult, time consuming and costly task.

Question 27

Define mean

Answer 27

Average value of all the scores. Calculated by adding all the values then dividing them by the number of values in a set of data.

Question 28

List advantages of calculating the mean

Answer 28

Simple to calculate and useful when comparing different sets of data.

Question 29

List disadvantages of calculating the mean

Answer 29

Can be effected by extreme values therefore it cannot tell us anything about the typical score.

Question 30

Define Median

Answer 30

The middle value of a given set of data when the values are arranged in ascending order.

Question 31

List advantages of calculating the median

Answer 31

Helps us find the average in a set that is affected by extreme values (doesn’t take into account anomalies).

Question 32

List disadvantages of calculating the median

Answer 32

More time consuming to calculate

Question 33

Define Mode

Answer 33

Most frequently occurring value in a set of data.

Question 34

List advantages of calculating the mode

Answer 34

Not affected by anomalies.

Question 35

List disadvantages of calculating the mode

Answer 35

Not the most accurate value because sometimes there might not be two of the same values occurring in the set of data or there may be more than one mode therefore the data becomes difficult to interpret

Question 36

Define range

Answer 36

The difference between the highest and lowest values in a set of data

Question 37

List advantages of calculating the range

Answer 37

Measured in the same units as the data and is easy to calculate.

Question 38

List disadvantages of calculating the range

Answer 38

Only depends on two of the values so it is a weak measure of spread in a small sample of data