Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

APPLIED MATHS 1 > DATA COLLECTION > Flashcards

DATA COLLECTION Flashcards

1
Q

Population

A

The whole set of items that are of interest

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

Census

A

Measuring every item of a population

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

Sample

A

Selection of observations taken from a portion of a population

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

Sampling unit

A

Each item that can be sampled

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

Explain: Simple Random Sampling

A

Every unit in the sampling frame has an equal chance of being selected. Use a number generator, or pull names from a hat, etc.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Pros and Cons: Simple Random Sampling

A

Pros: Bias free, easy and cheap. Cons: Not suitable for large populations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Explain: Systematic Sampling

A

Required elements are selected at regular intervals in an ordered list. Take every kth element where k=(Pop. size)/(Sample size) or N/n.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Pros and Cons: Systematic Sampling

A

Pros: Easy, suitable for large sample sizes. Cons: Sampling frame needed, can introduce bias.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Explain: Stratified Sampling

A

Sample size divided into groups/strata and then divided by the proportion needed overall (e.g 20% of 1000 units would be split into x amount of units, then 20% of the units would be observed)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Pros and Cons: Stratified Sampling

A

Pros: Good for large populations, gives an unbiased and fair view as proportional representation is guaranteed. Cons: dividing into groups can be difficult.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Explain: Quota Sampling

A

Sample size divided into groups based on characteristic, then chosen through deciding which units fit the quota the best. An interviewer selects the sampling units.

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

Pros and Cons: Quota Sampling

A

Pros: Allows a small sample to be representative of the population, can be inexpensive, allows for easy intercomparisons. Cons: When the sample size is larger, cost and time expense are added, can introduce bias, sorting into groups can cause bias and room for error.

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

Explain: Opportunity Sampling

A

Sampling units selected by interviewer at time of observance. Units all fit the criteria

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

Pros and Cons: Opportunity Sampling

A

Pros: Inexpensive, convenient, fast. Cons: Unlikely to provide a valid study, can be exposed to many forms of bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Name the three methods of random sampling

A

Simple random, Stratified, Systematic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Name the two methods of non random sampling

A

Quota, Opportunity

17
Q

A lake contains three different types of carp.
There are an estimated 450 mirror carp, 300 leather carp and 850 common carp.
Tim wishes to investigate the health of the fish in the lake.
He decides to take a sample of 160 fish.
Give a reason why stratified random sampling cannot be used.

A

A sampling frame is needed, and since it is impossible to find the exact population of fish in the lake, the population of fish cannot be divided into strata.

18
Q

Helen is studying one of the qualitative variables from the large data set for Heathrow from
2015.
She started with the data from 3rd May and then took every 10th reading.
There were only 3 different outcomes with the following frequencies
State the sampling technique Helen used.

A

Systematic sampling

19
Q

Name the four types of data values.

A

Qualitative, quantitative, continuous, discrete.

20
Q

What is a qualitative value?

A

A value that cannot be described with a number. E.G: Hair colour, which can be brown, blonde, red.

21
Q

What is a quantitative value?

A

A value that can be described by a number. E.G: Height, which can be 150cm, 156cm, 173cm, 185cm.

22
Q

What is a discrete variable?

A

A number that can only have a specific value. For example, you can only have a certain number of children; a family cannot have 4.5 children.

23
Q

What is a continuous variable?

A

A number that can have any value. For example, time: it can take 2.45 seconds to carry out a task, or 6.004, or 3677.6, or 0.00695, or 8.

24
Q

State the names of the five domestic stations in the Large Data Set.

A

Leeming, Leuchars, Camborne, Hurn, Heathrow

25
Q

State the names of the three foreign weather stations in the Large Data Set.

A

Beijing, Jacksonville, Perth.

26
Q

What three domestic stations in the LDS are on the coast?

A

Camborne, Hurn, Leuchars

27
Q

Units: Rainfall

A

millimeters. tr/trace means less than 0.05 mm.

28
Q

Units: Mean windspeed

A

knots. 1kn=1.15mph

29
Q

Units: total sunshine

A

1/10 of an hour

30
Q

Units: maximum gust

A

knots. 1kn=1.15mph

31
Q

Units: humidity

A

% of air saturated with water

32
Q

Units: mean visibility

A

decametres Dm of visibility

33
Q

Units: cloud cover

A

Oktas, meaning 1/8 of the sky covered in cloud

34
Q

Units: pressure

A

Hectopascal (hPa)

35
Q

What time periods were the LDS recorded within?

A
  1. May-October 1987. 2. May-October 2015
36
Q

What dates were the two Florida hurricanes?

A
  1. 12 October 1987. 2. 1-2 October 2015
37
Q

When was the UK Great Storm

A

15-16 October 1987

APPLIED MATHS 1 (2 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions