Week 2

Question 0

Dependent variable

Answer 0

A variable (often y) whose value depends on that of another. “Effect”

Question 1

Independent variable

Answer 1

Variable (often x) whose variation does not depend on that of another. “Cause”

Question 2

Confounds

Answer 2

Things that are going to interrupt your experiment.

Question 3

Research question

Answer 3

Addresses theory using a general question. More general than hypothesis.

Question 4

Hypothesis

Answer 4

Tentative statement derived from theory that specifies a relationship between specific concepts in form of prediction.

Question 5

Operationalise

Answer 5

Explicitly defining a way to measure something. Ie how to measure emotional intelligence

Question 6

Epistemological framework

Answer 6

How you conceptualise knowledge about the world.

Question 7

Basic research

Answer 7

Tries to answer basic/fundamental questions about the nature of behaviour. Doesn’t seek to solve problems. Based on curiosity.

Question 8

Lexicon

Answer 8

Mental dictionary

Question 9

Applied research

Answer 9

Conducted to address issues in which there are practical problems and potential solutions. Takes place in real world.

Question 10

Inter rater reliability

Answer 10

Getting another person to co-rate observations/data

Question 11

Extraneous variables

Answer 11

Any variable other than IV that could affect the dependent variable

Question 12

Normal distribution

Answer 12

A histogram that looks the same on both sides if a line is drawn down the centre. Majority of scores lie around the centre. Kurtosis and and skew are 0.

Question 13

Skew

Answer 13

Not a symmetrical distribution. Tall bars of graph clustered at one end of scale.

Question 14

Positive skew

Answer 14

Frequent scores clustered at lower end with tail pointing towards higher more positive scores

Question 15

Negative skew

Answer 15

Frequent scores clustered at higher end with tail pointing towards lower more negative score.

Question 16

Kurtosis

Answer 16

Degree to which scores cluster at the ends of the distribution (the tails). How pointy a distribution is.

Question 17

Positive kurtosis (leptokurtic)

Answer 17

Many scores in the tails (heavy distribution)

Question 18

Negative kurtosis (platykurtic)

Answer 18

Thin tails and flatter than normal.

Question 19

Central tendency M(italics) or X

Answer 19

Centre of a frequency distribution

Question 20

Mode

Answer 20

Score that occurs most frequently in the data. Can be more than one I.e. Bimodal, multi modal

Question 21

Median Mdn(italics)

Answer 21

Middle score when scores are ranked in order of magnitude. Calculated differently for odd and even # of scores

Question 22

Mean

Answer 22

Measure of central tendency. Add up all scores and \ by total # of scores. Can be influenced by extreme scores.

Question 23

Range of scores

Answer 23

Taking largest score and subtracting it from the smallest.

Question 24

Interquartile range IQR

Answer 24

Cut off top and bottom 25% of scores and calculate the middle 50% scores.

Question 25

Quartiles

Answer 25

3 values that split the sorted data into 4 equal parts.

Question 26

2nd quartile

Answer 26

Median - data is in 2 equal parts

Question 27

Lower quartile

Answer 27

Median of the lower half of data

Question 28

Upper quartile

Answer 28

Median of the upper half of data

Question 29

Quantile

Answer 29

Values that split the data into 4 equal portions.

Question 30

Percentiles

Answer 30

Points that split data into 100 equal parts

Question 31

Noniles

Answer 31

Points that split data into 9 equal parts.

Question 32

Deviance

Answer 32

Difference between each score and the mean

Question 33

Sum of squares

Answer 33

Adding up of squared deviances. Indicates total dispersion/total deviance of scores from the mean.

Question 34

Standard deviation

Answer 34

The squared root of the variance. Variance is the mean of the sum of squares. As SD gets larger distribution gets fatter.

Question 35

Small SD

Answer 35

Indicates that data points are close to the mean.

Question 36

Large SD

Answer 36

Data points are distant from the mean.

Question 37

Z score

Answer 37

Take each score and subtract it from the mean of all scores. Then divide by the SD. Used to calculate probability.

Question 38

N

Answer 38

Entire sample

Question 39

n

Answer 39

Subsample I.e. # of cases within a particular group