Topic 1 (statistics)

Question 1

Population

Answer 1

Complete set of items you are interested in

-individual items of population are known as sampling units

Question 2

Census

Answer 2

Measures a value from every member of the population

Adv
-get completely accurate view of population

Dis

• time consuming and expensive
• cant be used when testing process destroys items
• not possible with a changing population (continually)

Question 3

Sample

Answer 3

Selection observations from subset of population
info on whole population
Size = affect validity of conclusions (larger=accurate)
Different samples = different conclusions = natural variation in population

Adv

• quicker and cheaper than census
• fewer People respond= ( larger population)

Dis

• not be representative of original population
• not be large enough to give info about small minority sub-groups of population

Question 4

Sampling frame

Answer 4

When sampling units of a population are individually named or numbered to form a list called a sampling frame

Question 5

Parameter

Answer 5

Number that describes the entire population

Question 6

Statistic

Answer 6

Number taken from a single sample

Can use one or more of these to estimate the parameter

Question 7

Random sampling

Answer 7

Every member of population = equal chance of selection

Sample representative of population & removes bias from sample

Question 8

3 methods of random sampling

Answer 8

1. Simple random sampling
2. Systematic sampling
3. Stratified sampling

Question 9

Simple random sampling

Answer 9

Every sample of size n has equal chance of being selected
Need sampling frame, list — each thing allocated unique number and these numbers chosen at random

2 methods of choosing number

1. Lottery (placed in a hat)
2. Generating random nos (calculator/computer/random number table)

Adv
Fair way, probably representative of population, each sampling unit = same chance of being chosen

Dis
Not possible without sampling frame, time consuming/disruptive or expensive when large population, minority groups may be missed

Question 10

Systematic sampling

Answer 10

Chose starting point at random systematically select objectives a certain number apart
Only random when sampling frame has no order

Adv
Quick and easy suitable for large samples and large populations

Dis
Not possible without sampling frame
If sampling technique conincides with a periodic trait in population, sampling technique no longer representative = introduce bias
May be missing values in population and minority groups might be missed

Question 11

Stratified sampling

Answer 11

Population split into distinguishable groups different to each other and cover whole population groups are called strata within each group sample is selected

Adv
Minimises sample selection bias ensuring certain segments aren’t over or under represented
Frequencies for each sampled group proportional to frequencies for each group in population
Minor groups included and sample reflects whole population

Dis
Need sampling frame, strata must be carefully defined
Sometimes difficult to split population into naturally occurring groups

Question 12

How to decide on a sampling method

Answer 12

list every member of population
sources of bias/difficulties = taking certain samples
methods available = best suiting

Sampling method biased = sample that doesn’t represent population

Question 13

Types of non random sampling

Answer 13

1. Opportunity sampling
2. Quota sampling

(Volunteer sample: often biased only those passionate about that area being investigated may contribute their data/thoughts)

Question 14

Opportunity sampling

Answer 14

Taking sample from, target population available at time study is being carried out and fit criteria

Adv
East to select sample, inexpensive

Dis
Unlikely to produce a sample representative of population
Highly dependant on individual researcher ‘pick nice people’ = biased

Question 15

Quota sampling

Answer 15

Population split into groups like stratified
Size of each group determines proportion of sample having characteristic
Judgement is used to select members and the quotas are filled by interviewers

Adv
Even small sample representative of population, no sampling frame needed, quick easy inexpensive and different group responses can be compared

Dis
Non random could be biased, split into groups = inaccurate or time consuming
Non responses aren’t recorded may distort interpretations

Different to stratified = as could be biased when choosing the people once in groups not everyone gets a chance of selection stratified is random

Question 16

Quantitative data

Answer 16

Associated with numerical observations
Can be continuous (can take any value in a given range you measure it ) or discrete (only takes specific value in a given range often count in)

Question 17

Qualitative data

Answer 17

Associated with non-numberical observations

Question 18

Large data set places

Answer 18

from west to east then south to north 
Camborne = coastal 
Hurn = coastal 
Heathrow = inland 
Leeming = inland 
Leuchars = coastal 

Jacksonville (NH)= coastal
Beijing (NH)=inland
Perth (SH)=coastal

Question 19

things to be aware of for each large data location

Answer 19

1. coastal or inland
2. hilly or flat
3. distance fish from equator

(need basic geographical knowledge e.g. coastal = windy, mountains = rain and changeable)

Question 20

recording data

Answer 20

-reading not avaliable = n/a
-total amount of rain fall less than 0.05 = trace of rain
-relative hummdities above 95% = associated with mist and fog
-1 knot is 1.15 mph
-cloud cover = okras 0 = clear sky and 8 = overcast
-pressure = hectopascal
(sheet in folder)

Question 21

statistic

Answer 21

random variable that is a function of sample which contains no unknown quantities/parameters
(solely/only known)