Large data set + sampling Flashcards

1
Q

5 Uk weather stations

A

(N to S)
1. Leuchars
2. Leeming
3. Heathrow
4. Hurn
5. Camborne

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

3 international weather stations

A

Northern Hemisphere:
(W to E)
1. Jacksonville
2. Beijing

Southern Hemisphere:
- Perth

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

When was the data collected?

A
  • May-Oct 1987
  • May-Oct 2015
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Variables

A
  1. total rainfall (mm)
  2. mean temp (oC)
  3. total sunshine (hrs to nearest 0.1)
  4. mean windspeed (kn)
  5. max gust (kn)
  6. humidity (%)
  7. mean visibility (m)
  8. mean pressure (hPa)
  9. wind direction
  10. mean cloud cover (oktas)
  • 1kn = 1.15 mph// beaufort scale (0-5)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Mean wind speed- UK vs other countries

A
  • UK ~9nm
  • Beijing- 4nm
  • Jacksonville- 5nm
  • Perth- 8nm
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Temp range

A
  • large range in Beijing
  • Jacksonville- highest min
  • Perth ~UK
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

How to carry out simple random sampling

A
  • allocate a no. between 1 &N to each person in sampling frame
  • use random no. tables/ computer/ calculator to select n (context) diff. no. between 1 & N
  • people corresponding to these no. become the sample
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

➕ of simple random sampling

A
  1. x bias
  2. easy & cheap
  3. each no. has a known equal chance of being selected
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

➖ of simple random sampling

A
  1. x suitable w/ large pop size
  2. sampling frame needed
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

How to carry out systematic sampling?

A

(required elements are chosen at regular intervals)

  • randomly select a no. between 1 & k (eg. 001 & 500// 00 & 499)
  • select every kth element
    – k = pop size/ sample size (eg. k= 50000/100 = 500)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Population def

A

whole set of items of interest

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Sample def

A

subset of pop intended to represent the pop

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is data collected from the entire pop?

A

census

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

+ & - of census

A

+ completely accurate result

  • time consuming & expensive
  • x used when testing involves destruction (eg. light bulbs)
  • large vol of data to process
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

+ & - of census

A

+ completely accurate result

  • time consuming & expensive
  • x used when testing involves destruction (eg. light bulbs)
  • large vol of data to process
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

+ & - of sample

A

+ cheaper
+ quicker
+ ↓ data to process

  • data might x accurate
  • data may x large enough to represent small sub-groups
16
Q

How to carry out stratified sampling?

A
  • pop divided into groups (strata)
  • simple random sampling in each group
  • same proportion from each strata
    – sample size/ pop size
  • large sample
  • naturally divided into groups
17
Q

+ of stratified sampling

A
  1. reflects pop structure
  2. proportional representation of groups within pop
18
Q
  • of stratified sampling
A
  1. pop must be clearly classified into distinct strata
  2. selection within each stratum–> - of simple random sampling
19
Q

+ of systematic sampling

A
  1. simple & quick
  2. √ large samples
20
Q
  • of systematic sampling
A
  1. √ sampling frame
  2. bias if s frame x random (eg. surname)
21
Q

How to carry out quota sampling?

A
  • pop divided into groups acc. to characteristics
  • quota of items in each group–> reflects that group’s proportion in whole pop
22
Q

+ of quota sampling

A
  1. small sample- still representative of pop
  2. x sampling frame
  3. quick, easy, cheap
  4. easy comparison betw. diff. groups
23
Q
  • of quota sampling
A
  1. non-random–> bias
  2. pop must be divided into groups–> costly/ inaccurate
  3. non-responses–> x recorded
24
Q

Carry out opportunity/ convenience sampling

A
  • from ppl available at the time of study
  • & meet criteria
25
Q

+ of opportunity sampling

A
  1. easy
  2. x expensive
26
Q
  • of opportunity sampling
A
  1. x representative
  2. highly dependent on researcher (making assumptions- eg. assuming sb’s race w/o asking)
27
Q

3 types of data

A
  1. qualitative/ categorical
  2. discrete quantitative
  3. continuous quantitative
28
Q

Which months included have 30 days?
(for calculating mean)

A

June + Sept

29
Q

Which UK locations are inland?

A

Leeming, Heathrow

30
Q

Which country is in the Southern hemisphere?

A

Perth (Australia)
- weather opp. to everywhere else

31
Q

What does daily total rainfall include?

A
  • rain
  • melted snow + hail
32
Q

Which variables are UK only?

A
  • daily total sunshine
  • daily max relative humidity
  • daily max gust
  • daily mean wind direction (direction blowing from)
  • daily max gust direction
  • visibility
  • daily mean total cloud
33
Q

What are typical values of daily mean pressure?

A

988-1038 hPa