Applied Maths Flashcards
A population is
The whole set of items that are of interest
A sample is
Some subset of the population intended to represent the population.
Sampling unit
Each individual thing in the population that can be sampled
Sampling frame
Often sampling units of a population are individually named or numbered to form a list
Census
Data collected from the entire population
Census pros and cons
Should give you a completely accurate result
Time consuming and expensive
Cannot be used when testing involves destruction
Large volume of data to process
Sample pros and cons
Cheaper, quicker, less data to process
Data may not be accurate
Data may not be large enough to represent small sub-groups
Random sampling
Each sampling unit in our sampling frame has an equal chance of being selected (avoids bias)
How to carry out random sampling
In sampling frame each item is assigned a number. Use random number generator or lottery sampling
Random sampling Pros and cons
Bias free, easy and cheap to implement, each number has a known equal chance of being selected
Not suitable when population size is large, sampling frame needed
Systematic sampling
Required elements are chosen at regular intervals in ordered list
How to carry out systematic sampling
Take every kth element where: k=population size/ sample size starting at random item between 1 and k
Systematic sampling Pros and cons
Simple and quick to use, suitable for large samples and populations
Sampling frame required
Can introduce bias if sampling frame not ramdom
Stratified sampling
Population divided into groups (strata) and a simple random sample carried out in each group.
Used when sample is large and population naturally divides into groups
How to carry out stratified sampling
Same proportion (sample size/ population size) sampled from each strata
Stratified sampling Pros and cons
Reflects population structure, guarantees proportional representation of groups within population
Population must be clearly classified into distinct strata, selection within each strata suffers from same disadvantages as simple random sampling
Quota sampling
Population divided into groups according to characteristic. A quota of times/ people in each group is set out to try and reflect the group’s proportion in the whole population
How to carry out quota sampling
Interviewer selects the actual sampling units
Quota sampling Pros and cons
Allows small sample to still be representative of population
No sampling frame required
Quick easy inexpensive
Allows for quick and easy comparison between different groups in population
Non random sampling can introduce bias
Population must be divided into groups, could be costly and Inaccurate
Increasing scope of study increases number of groups, adding time) expensive
Non-responses are not recorded
Model assumptions (light)
It’s mass is very small (regarded as zero), such as a string or pulley, tension is the same at both ends of a light string
Modelled assumption (particle)
Dimensions of the object are negligible. It’s mass is concentrated at a single point. Air resistance and rotational forces can be ignored.
Modelling assumptions (inextensible)
Does not stretch under a load. Acceleration in constant in objects connected by a taut inextensible string
Uniform acceleration
Constant acceleration
Retardation
Deceleration
If there’s no air resistance for a falling object it’s acceleration is..
Constant