7 Research Methods (2)

Front 1

operationalising IV and DV

Back 1

turning them into factors that can be observed and measured

Hint 1

IV: caffeine intake

operationalised as: the amount of coffee or soft drinks in a day

DV: sleep

operationalised as: the amount of sleep an individual gets each night

Front 2

extraneous variables

Back 2

a variable other than the IV that can cause a change in the DV.

extraneous variables are usually found before the experiment is conducted and controlled so there is no effect on the DV

Front 3

participant variables
(types of extraneous variables)

Back 3

the individual characteristics of the participants that affect the experiment

e.g age, gender, mood, cultural background

Front 4

situational variables
(types of extraneous variables)

Back 4

any variable associated with the experimental situation

e.g environment, temperature, time of day

Front 5

experimenter variables
(types of extraneous variables)

Back 5

variables associated with the researcher conducting the experiment

e.g mood, if there are multiple experimenters, appearance, treatment of participants

Front 6

confounding variables

Back 6

a variable other than the IV that has made an affect on the DV during the experiment

Front 7

correlational studies

Back 7

a non-experimental research method used to investigate the relationship between two or more variables.

it doesn't say if it causes the other variable to occur, but it shows the relationship between the variables

e.g air temperature and violent crimes

Front 8

positive correlation

Back 8

means that two variables change in the same direction; as one increases so does the other, or if one decreases, so does the other

Front 9

negative correlation

Back 9

means that two variables move in opposite directions; as one variable increases, the other tends to decrease and vice versa

Front 10

correlation coefficient

Back 10

a number expressed as a decimal that describes the direction (whether it is positive or negative)

+ 1.00 or - 1.00

Front 11

strength of correlation

Back 11

a correlation coefficient that is closer to + 1.00 means it has a strong relationship

- 0.13 would be a weak negative correlation

+ 0.13 is a weak positive relationship

Front 12

scatter plots

Back 12

a graph with two different variables, dots are placed on the corresponding place of the axis.

by drawing a line across the graph you can tell if the relationship is strong, moderate or weak

Front 13

descriptive statistics

Back 13

organise, summarise and describe raw data so it can be interpreted

Front 14

normal distribution

Back 14

most of the data is located around the centre, with scores extremely high or extremely low either side of the middle, giving a symmetrical appearance

Front 15

positively skewed

Back 15

a curve skewed to the left, indicating there is a large number of low scores than high

Hint 15

think opposite of positive

Front 16

negatively skewed

Back 16

a curve skewed to the right, indicating a large number of high scores

Hint 16

think opposite of negative

Front 17

mean

(measures of central tendency)

Back 17

the average

calculated by adding all the scores together and dividing by the number of scores there are

3 + 3 = 6

6/2 = 3

use when there is a normal distribution

Front 18

median

(measures of central tendency)

Back 18

the middle score

calculated by arranging all scores from lowest to highest or vice versa and finding the middle score

use when the scores are in a skewed distribution

Front 19

mode

(measures of central tendency)

Back 19

the most frequently occurring score

calculated by finding what score occurs the most

Front 20

variability

Back 20

the spread of scores

Front 21

low variability

Back 21

if the scores are packed tightly around the mean

Front 22

high variability

Back 22

if the scores are spread out across the graph

Front 23

range

(measures of variability)

Back 23

the score that describes the difference between the highest and lowest score on a graph.

calculated by subtracting the lowest score from the highest

e.g 21 - 17 = 4

Front 24

variance

(measures of variability)

Back 24

the spread of scores around the mean

calculated by:

if the mean was 50, and a score was 60, it is +10

if a score was 40, it would be - 10

the variance is then all added up together or cancelled out

Front 25

standard deviation

(measures of variability)

Back 25

summarises how far every score differs from the mean

calculated by:

taking the square root of the variance score

if there is a high standard deviation there is more variability, if there is a low standard deviation there is a low variability

Front 26

reliability

Back 26

the consistency, dependability and stability of the results.

if the experiment is going to be repeated, the results should be similar

Front 27

validity

Back 27

the experiment accurately measures what it is supposed to measure

e.g using a cloth tape that has been stretched to measure waist length does not have validity as it does not accurately measure the waist length

Front 28

internal validity

Back 28

techniques used to measure the IV and DV in the experiment are accurate

Front 29

external validity

Back 29

the conclusions can be generalised to the population

Front 30

reporting conventions

Back 30

* Title
* Abstract (summary of entire report - aim, hypothesis, participants, method, results, conclusion, generalisation)
* Introduction (background info, definition, discussion of theories, aim, hypothesis, variables)
* Method (participants - total number, gender, age, characteristics, sampling procedure) then materials in dot point formation
* Procedure - step by step
* Results (descriptive stats) + describe what is shown in the table/graph
* Discussion (restate hypothesis, whether supported or not, discuss results and statistical significance, confounding variables and limitations (do to with participants), talk about generalisation)