Unit 4 - Statistics Flashcards

1
Q

Types of Quantitative data

A
  • Discrete: Can be counted, has a finite value. (E.g. Number of cats in this house)
  • Continuous: Has no finite value (E.g. Age, Height, Weight, Temperature)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Define Primary Data and its ads and dads

A
  • Data collected ourselves.
  • Ads: Being collected with specific purpose in mind. You know how the data was collected.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Define Secondary data and its ads and dads

A
  • Data collected by someone else.
  • Dads: Could have been collected for a different purpose. Cannot know how data was collected. Unable to know validity of data.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Define reliable data

A

If you repeat data collection, result will be similar.

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

Define sufficient data

A

Enough data is available to support your conclusions.

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

Define Target population

A

Population from where you want to take a sample.

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

Define Sampling frame

A

List of items/people from which you can take your sample.

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

Define Sampling unit

A

A single member from the sampling frame that is chosen to be sampled.

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

Define Sampling variable

A

The variable under investigation. The characteristic you want to measure from each sampling unit.

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

Define Sampling values

A

The possible values which the sampling variable can take.

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

Explain Random Sampling and its ads and dads

A
  • How it works: In a sampling frame, each item has an identifying number. Use random number generator. Every sample has equal chance of being chosen.
  • Ads: Bias free, easy, cheap, equal chance.
  • Dads: Not suitable with large population size, sampling frame required.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Explain Stratified Sampling

A
  • How it works: Population divided into groups (strata) and random sampling carried out in each group. Same proportion sampled from each group.
  • Ads: Reflects population structure, guarantees proportional representation of groups within population
  • Dads: Population must be clearly classified into distinct strata, selection within each stratum suffers same disadvantage as random sampling.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Explain Systematic Sampling and its ads and dads

A
  • How it works: required elements are chosen at regular intervals in ordered list.
  • Ads: Simple and quick to use, suitable for large samples/populations.
  • Dads: Sampling frame required, can be bias.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Explain Quota sampling and its ads and dads

A
  • How it works: Population is divided into groups according to characteristics. A quota of items/people in each group is set to try and reflect group’s proportion in the whole population. Interviewer selects actual sampling units.
  • Ads: Allows small sample to still be representative of population, No sampling frame required, quick, easy, cheap.
  • Dads: bias, dividing characteristics may be inaccurate, increasing scope increases time and cost, non-responses not recorded.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q
A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly