1
Q
What is a population?
A
A population is the whole set of items that are of interest
2
Q
What is a sample?
A
A sample is some subset of the population intended to represent the population
3
Q
What is a sampling unit?
A
Each individual thing in the population that can be sampled is known as a sampling unit
4
Q
What is a sampling frame?
A
Often sampling units of a population are individually named or numbered to form a list called a sampling frame
5
Q
What is a census?
A
Data collected from the entire population is known as a census.
Data can either be collected from a sample, or from the entire population.
6
Q
What are the advantages of a census?
A
- Should give completely accurate result
7
Q
What are the disadvantages of a census?
A
- Time consuming and expensive
- large volume of data to process
- can not be used when testing involves destruction
8
Q
What are the advantages of a sample?
A
- Cheaper and quicker
- less data to process
9
Q
What are the disadvantages of a sample?
A
- May not be accurate
- Data may not be large enough to represent small sub-groups
10
Q
Simple random sampling - how to carry out
A
- First give each sampling unit an identifying number.
- Use random number generator or ‘lottery sampling’
11
Q
Simple random sampling - advantages
A
- Bias free
- Easy and cheap to implement
- Each number has a known equal chance of being selected
12
Q
Simple random sampling - disadvantages
A
- Not suitable when population size is large
- Sampling frame needed
- May not be representative of population (depending on size of sample, if small)
13
Q
Systematic sampling - how to carry out
A
- Required elements are chosen at regular intervals in ordered list.
- For example, take every kth elements where: K= population size (N) / sample size (n) starting at random item between 1 and k.
14
Q
Systematic sampling - advantages
A
- Simple and quick to use
- Suitable for larger samples/ population
- More likely to be representative
15
Q
Systematic sampling - disadvantages
A
- sampling frame again needed
- can introduce bias if sampling frame not random
16
Q
Stratified sampling - How to carry out
A
Population is divided into groups (strata) and a simple random sample is carried out in each group.
- Same proportion sampled from each strata.
- population size (N) / sample size (n)
- Used when sample is large and population naturally divides into groups
17
Q
Stratified sampling - advantages
A
- Reflectes population structure
- Guarantees proportional representation of groups within population
18
Q
Stratified sampling - disadvantages
A
- Population must be clearly classified into distinct strata
- Selection within each stratum suffers from same disadvantages as simple random sampling
19
Q
Quota sampling - How to carry out
A
- Population is divided into groups by different characteristics
- A quota of items/ peoples in each group is set to try and reflect the group’s proportion
- Interviewer selects the actual sampling units
20
Q
Quota sampling - advantages
A
- Allows small sample to still be representative of population
- No sampling frame required
- Quick, easy, inexpensive
- Allows for easy comparison between different groups in population
21
Q
Quota sampling - disadvantages
A
- Non-random sampling can introduce bias
- Population must be divided into groups, which can be costly
22
Q
Opportunity sampling - how to carry out
A
- Sample taken from people who are available at the time of study, who meet criteria
23
Q
Opportunity sampling - advantages
A
- Easy to carry out
- inexpensive
24
Q
Opportunity sampling - disadvantages
A
- Unlikely to provide a representative sample
- Highly dependant on individual researcher
- Non responses are recorded
- Increased scope of study increases number of groups, adding time/expense
25
Random and non-random sampling methods
Random sampling:
- Simple random sampling
- Systematic sampling
- Stratified sampling
Non-random sampling:
- Quota sampling
- Opportunity sampling
26
What is variants?
- Variants is a measure of spread that takes all values into account.
- Variants, by definition, is the average squared distance from the mean
27
What is an outlier?
- An outlier is an item which is inconsistent with the rest of the data.
- One common definition of an outlier of an outlier is when we're 1.5IQR's beyond the lower and upper quartiles
- Another definition of an outlier is 2 standard deviations from the mean
28
What is discrete data?
Data that can only take specific values.
29
What is continuous data?
Data that can take any value within a range.
30
What are bar charts and histograms for?
Discrete or continuous data?
Bar charts - for discrete data
Histograms - for continuous data
31
What does two variables having a casual relationship mean?
- Two variables have a casual relationship if a change in one directly causes a change in the other.
- Just because two variables show correlation it does not necessarily mean that they have a casual relationship.
32
What is interpolating?
Interpolating is estimating a value inside the data range.
33
What is extrapolating?
Extrapolating is estimating a value outside the data range.
34
What is cluster sampling?
Cluster sampling involves dividing the population into distinct groups, or 'clusters', then randomly selecting a certain number of these clusters for inclusion in the sample.
35
What is a self-selected sample?
- A self-selected sample is simply one in which the respondent put themselves forward for participation in a survey or similar form or research.
- Possibility for bias is extremely high
36
What are symmetrical distributions?
- Symmetrical distributions are probability distributions where the left side mirrors the right side.
- This property indicates that the mean, median and mode os the distributions are all located at the centre.
37
What is unimodal distribution?
- A unimodal distributions is a distribution that has one clear peak.
- The values increase first, rising to a single highest point where they then start to decrease.
- A unimodal distribution can either be symmetrical or non symmetrical.
38
What is bimodal distribution?
A bimodal distribution has two distinct peaks - showing that data points are distributed across two separate values.
39
What is bivariate data, association, and correlation?
- Bivariate data consists of two variables for each member of the population.
- An association between the two variables is some kind of relationship between them.
- Correlation measures linear relationships.
40
What is a regression line?
- A regression line is defined as a mathematically determined line of best fit that represents the functional relationship between two variables, allowing for the prediction of one variable based on the known value of another.
- Remember correlation does not cause causation
41
What does it mean if two events are mutually exclusive?
If two events are mutually exclusive they can't happen at the same time.
42
If two events are mutually exclusive then...
- P(A and B) = 0
- P(A or B) = P(A) + P(B)
43
What does it mean if two events are independent?
If two events are independent then whether one event happens does not affect the probable;oty of the other happening.
44
If A and B are independent then...
- P(A and B) = P(A) x P(B)
45
What is a discrete random variable?
Discrete random variables are variables that can only take distinct values; they can change each time they are measured.
46
You can model a random variable X with a binomial distribution B(n,p) if... (4 conditions)
- there are a fixed number of trials
- there are two possible outcomes, 'success' and failure
- there is a fixed probability of success, p
- the trials are independent of each other
47
What does discrete uniform distribution mean?
In probability theory and statistics, the discrete uniform distribution is a symmetric probability distribution wherein each of some finite whole number n of outcome values are equally likely to be observed. Thus every one of the n outcome values has equal probability 1/n.
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