What is a population?
A population consists of all the items that are of interest
What is a sample?
A sample is a subset of items chosen from a population
What is a sampling unit?
Each individual item in the population that can be sampled
What is the sampling frame?
An ordered (numbered) list of sampling units
What is a census?
data collected from the entire population
What are the advantages of a census?
It should give completely accurate results
What are the advantages of a sample?
- Less expensive
- Less time consuming
- Less data to process
What are the disadvantages of a census?
- Time consuming and expensive
- Cannot be used when testing involves destruction
- Large volumes of data to process
What are the disadvantages of a sample?
- Data may not be accurate
- Sample may not be large enough to represent small sub-groups of the population
What is random sampling?
When each member of the population has an equal chance of being chosen in order to avoid bias
What are the 3 types of random sampling?
- Simple Random
- Systematic
- Stratified
What is the method for a simple random sample?
To carry out a simple random sample, size n, from a population size N, firstly you need a sampling frame.
Each item is assigned a different number from 1-N. Use a random number generator to select n unique numbers
Choose the items corresponding to these numbers to form the sample
What is the method for a systematic sample?
To carry out a systematic sample, size n, from a population size N, you need a samplin frame.
Each item is assigned a random number from 1-N. K = N/n. Use a random number generator to select a random number between 1 and N, starting with this number, take every Kth element to form the sample.
What is the method for a stratified sample?
To carry out a stratified sample, size n, from population size N, you need a sampling frame and distinct strata. The same proportion (n/N) is to be sampled from each strata
Within each strata, each item is assigend a different number and a random number generator is used to select the number of unique numbers required.
Choose the items corresponding to these numbers to form the sample
What is a systematic sample?
The required elements are chosen at regular intervals from an ordered list
What is a stratified sample?
Population is divided into groups (strata) and a simple random sample is carried out in each group
What are the advantages of simple random sampling?
- Easy and cheap to implement for small populations and samples
- Each sampling unit has an equal chance of being seleceted and it is therefore bias free
What are the disadvantages of simple random sampling?
- Not suitable when population size is large
- Sample may not accurately reflect the population
- A sampling frame is needed
What are the advantages of systematic sampling?
- Simple and quick to use
- Suitable for large samples and populations
What are the disadvantages of systematic sampling?
- Can introduce bias if sampling frame is small and not random as patterns can be picked up in the data
- A sampling frame is needed
What are the advantages of stratified sampling?
- Sample accurately reflects population structure
- Guarantees proportional representation of groups within population
What are the disadvantages of stratified sampling?
- Sampling frame is needed and population must be clearly classified into distinct strata
- Selection within each stratum suffers from same disadvantages as simple random sampling
What are the 2 types of non-random sampling?
- Quota Sampling
- Opportunity/Conveninnce Sampling
What is quota sampling?
- The population is divided into groups according to characteristic.
- A quota of items in each group is set to try and reflect the group’s proportion in the whole population (quoatas calculated in the same way as stratified sampling).
- Interviewer selects the actual sampling units until the quotas are reached.
- Once a quota is full, ignore any subsequent sampling units that also meet the characteristic
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Chapter 1 Data Collection (AS)36
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Chapter 1 Large Data Set (AS)29
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Chapter 2 Measures of Location and Spread (AS)25
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Chapter 3 Representations of Data (AS)7
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Chapter 4/1 Correlation/Regression (AS/A-Level)16
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Chapter 5/2 Probability (AS and A-Level)23
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Chapter 6 Statistical Distribution (AS)1
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Chapter 7 Hypothesis Testing (AS)1
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Chapter 3 Normal Distribution (A-Level)0
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Chapter 8 Modelling in Mechanics (AS)22
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Chapter 9 Constant Acceleration (AS)6
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Chapter 8: Further Kinematics (Vectors) A-Level9
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Chapter 6: Projectiles11
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Chapter 4 Moments13
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Chapter 5 Forces and Friction8
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Chapter 7 Application of Forces7
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Lifts4
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Pulleys1
