1 Data collection

Question 1

Large Data set

Answer 1

A huge spreadsheet of data covering weather records in 1987 and 2015

Question 2

Population

Answer 2

The whole set of items that are of interest

Question 3

Quota sampling

Answer 3

A non random method of sampling where the sample reflects the characteristics of the population

Question 4

Quantitative data

Answer 4

Data which is numerical e.g. height

Question 5

Discrete data

Answer 5

Data that can only take certain values e.g. ( number of students in a class, there can’t be half a student)

Question 6

Sampling frame

Answer 6

A list of sampling units

Question 7

Sample

Answer 7

A selection of observations taken from a population

Question 8

Continuous

Answer 8

Data that can take any value in a given range e.g. time in a race

Question 9

Qualitative

Answer 9

Data which is not numerical but fits into categories e.g. eye colour

Question 10

Random

Answer 10

When every item in the population has an equal chance of being chosen for the sample

Question 11

Systematic

Answer 11

A random method of sampling where items are chosen at regular intervals from an ordered list

Question 12

Stratified

Answer 12

random sampling where the population is divided into strata (eg males and females) and then randomly picked from them

Question 13

Census

Answer 13

Used to observe every member of the population

Question 14

Opportunity

Answer 14

Non random method which consists of taking a sample from the items available to you at a certain time

Question 15

Sampling unit

Answer 15

Individual units of a population

Question 16

Census pros and cons

Answer 16

+ should give a completely accurate result

• time consuming
• expensive
• large quantities of data

Question 17

Sample pros and cons

Answer 17

+quick
+cheap

• may not be that accurate
• sample may not be large enough to give information about subgroups

Question 18

Simple random sampling pros and cons

Answer 18

+free of bias
+easy and cheap for small sample
+each sampling unit has a known and equal chance of selection

• not suitable for large numbers
• a sample frame is needed

Question 19

Stratified sampling pros and cons

Answer 19

+sample accurately reflects the population structure
+guarantees proportional representation of groups within a population

• population must be split into distinct strata
• selection within each stratum suffers from same cons as random sampling

Question 20

Systematic sampling pros and cons

Answer 20

+simple and quick to use
+suitable for large samples and large populations

• a sampling frame is needed
• it can introduce bias if the sampling frame is not random

Question 21

Quota sampling pros and cons

Answer 21

+allows a small sample to still be representative of the population
+no sampling frame required
+quick, easy and inexpensive
+allows for easy comparison between different groups within a population

• could be biased
• population must be divided into groups, which can be costly and inaccurate
• increasing scope adds time and expense
• non responses are not recorded

Question 22

Opportunity sampling pros and cons

Answer 22

+easy to carry out
+cheap

• unlikely to provide a representative sample
• highly dependent on the individual researcher