13 - Statistics – organising the data

Question 1

Raw data/ scores

Answer 1

Untreated, unconverted values obtained directly from measuring process used in a study.

Question 2

Categorical variable

Answer 2

Variable where cases are merely placed into independent, separate categories.

Star sign

JUST ONE category.

Question 3

Measured variable

Answer 3

Variables where cases measured on it are placed on some sort of scale that has direction.

Any other sort of variable above the level of mere categorising.

Question 4

In many experimental studies

Answer 4

Independent variable = Categorical Variable

Normal or hot room = categorical

Dependent variable = Measured variable

Aggression rating = measured

Question 5

Levels of measurement

Answer 5

Levels at which data are categorised or measured.

Question 6

Nominal measurement

Answer 6

Level of measurement at which numbers are only labels for categories

Associated with categorical classification system.

“Tall” and “Short”

Question 7

Ordinal measurement

Answer 7

Levels of measurement at which cases are arranged in rank positions. (ranking scale)

Tallest to shortest

Gives more information than “Nominal”, but still lacks a lot.

Question 8

Interval

Answer 8

Level of measurement at which each unit on a scale represents an equal change in the variable measured.

Measures every person.

Question 9

Coding (nominal)

Answer 9

Giving “dummy” numbers to discrete levels of an independent variable. (because of system)

Example: studying education level.

High School = 1

Bachelor’s degree = 2

Master’s degree = 3

Question 10

Frequent data/ frequencies

Answer 10

Numbers of cases in specific categories.

Example: 10 people said High School = 10 Frequency data ^

Question 11

Quasi-interval scale (interval level of measurement)

Answer 11

Scale that appears to be interval but where equal intervals do not necessarily measure equal amounts of the construct.

Example: IQ scale. 120 IQ vs. 100 IQ, does not mean the other person is 20% more intelligent. ?

Not calibrated from a Zero-Point

Question 12

Ratio Scales

Answer 12

interval-type scale where proportions on the scale are meaningful; usually an absolute zero exists.

Example: weight (kg)

Calibrated from a zero-point

Question 13

Changing data from one level to another

Answer 13

You can only go downwards.

Question 14

Median split method

Answer 14

dividing a set of measured values into two groups by dividing them into high and low at their median.

Example: Having done an interval score on people anxiety and finding the median (average) and placing everyone above that in “high” category and everyone below in “low” category.

Question 15

Continuous scale/ variable

Answer 15

scales where there are no discrete steps; theoretically, all points along the scale are meaningful.

Example: age

Question 16

Discrete scale/ variable

Answer 16

Scale on which not all subdivisions are meaningful; often one where the underlying construct to be measured can only come in whole units

Example: number of children.

Question 17

Data set

Answer 17

Group of data points or values which can be summarised or analysed.

Example: Premier League Table

Question 18

Central Tendency

Answer 18

Formal term for any measure of the typical or middle value in a group

Mean

Median

Mode

Question 19

Dispersion

Answer 19

technical and general term for any measure of the spread of values in a sample of data or population.

Basically: not only showing the average or median, but how much the numbers vary. All the grades amongst the different grades.

Question 20

Mean (arithmetic)

Answer 20

Average of values found by adding them all and dividing by the number of values in the set.

How to calculate grade average

Question 21

Outliers

Answer 21

“Rogue” values at an extreme distance from the centre of the data set. Can be removed from analysis, but must be reported.

Question 22

Trimmed Mean

Answer 22

The mean of a data set with its most extreme 5% of values removed.

Example: Removing 2.5% of the highest and 2.5% of the lowest score.

Question 23

Median

Answer 23

Measure of central tendency; middle value of data set.

Basically: sort numbers (rising) to find the middle. If two in middle. Add and divide by 2

Example: 2,4,7,9,12

Question 24

Median position/location

Answer 24

Position where median is to be found in an ordered data set.

Basically: just the position. Number 5 in a row of 10

Question 25

Class Intervals

Answer 25

Categories into which a continuous data scale can be divided in order to summarise frequencies.

Example: 0-10 years, 11-20 years etc…

Question 26

Model/modal value

Answer 26

Measure of central tendency – most frequent value in data set

Example: if 5 is the most said score on a movie, the modal value is 5.