Lecture 2A: Descriptive Stats And Distributions

Question 1

Nominal data

Answer 1

Aka categorical or qualitative variables

Eg eye colour, socio-economic status, marital status, nationality or gender

Question 2

Numerical data

Answer 2

Aka score or quantitative variables

Eg age, weight, height, IQ, test scores

Question 3

Nominal

Answer 3

Placing cases into named categories (eg nationality)

Question 4

Ordinal

Answer 4

This ranks cases based on their order on a given variable (eg 1st, 2nd, 3rd)

Question 5

Interval

Answer 5

Where the distances between the sequential points on the scale are equal (eg scores on a test 1-40)

Question 6

Ratio

Answer 6

Same as interval but with an absolute zero (eg time in seconds)

Question 7

Kurtosis

Answer 7

To do with the shape of the curve

How much of the distribution is in the tails of the curve (how many people are at the extremes)

Question 8

Mesokurtic

Answer 8

A normal curve.

SPSS reports 0 for kurtosis

Question 9

Leptokurtic

Answer 9

A steel curve (with very few people in the tails)

Kurtosis is a positive value

Question 10

Platykurtic

Answer 10

A flat curve (with lots of people in the tails)

Kurtosis is a negative value

Question 11

Bimodal distribution

Answer 11

Literally means ‘two modes’

Two humps on the graph

Question 12

Measures of central tendency

Answer 12

Mode
Median
Mean

Question 13

Measures of variability

Answer 13

Range
Interquartile range
Variance
Standard deviation

Question 14

Simple random sampling

Answer 14

Every individual in the population has an equal chance of being part of the sample
Eg a lottery where everyone has one ticket
Eg 100 people chosen at random from the electoral roll

Question 15

Systematic sampling

Answer 15

Sample chosen from list of all individual in population by selecting every kth individual

Question 16

Stratified sampling

Answer 16

The population is divided into strata (subgroups), and then a random sample is selected from each of the strata

Question 17

Cluster sampling

Answer 17

Clusters (groups) are selected from the population, and then a random sample of individuals are taken from each of the selected clusters

Question 18

Convenience sampling

Answer 18

Sample is drawn from an accessible population

Eg asking Psych students to participate in research

Question 19

Quota sampling

Answer 19

Population broken into categories, then participants selected based on reaching a specific proportion
Eg psychology students recruited until quota for each gender filled

Question 20

Purposive sampling

Answer 20

Selecting people from a particular category based on the focus of the research
Eg selecting families with children; selecting people with credit cards

Question 21

Snowball sampling

Answer 21

Recruit participants based on recommendations from already recruited participants

Question 22

Sampling error

Answer 22

Some of the error in research is due to using a sample rather than the entire population.
Is the differences between sample data (statistics) and population data (parameters).
More likely to have a large sampling error if you don’t use random sampling or have a small sample

Question 23

Standard error

Answer 23

A common way of measuring sampling error.
The standard deviation of the sampling distribution of a statistic.
Eg pick 100 students and find the mean. Pick another 100 students and find the mean. Do this again and again.
The standard deviation of these means is known as the standard error

Question 24

Confidence intervals

Answer 24

Provide an interval estimate of a parameter - a range within which the parameter is likely to fall