Topic 1 - Statistical Sampling

• Simple Random sampling - Advantages

  Easy and cheap to implement for small samples and populations, Free of bias, Each sampling unit has an equal chance of selection.
• Simple Random sampling - Disadvantages

  A sample frame is needed (A list, A certain range, etc), Would not be suitable for a large population due to being expensive, disruptive and time consuming.
• Population


  The whole set of items that are of interest
• Census


  Observes or measures every member of a population
• Advantages of a census

  It should give a completely accurate result
• Disadvantage of a census

  Time consuming and expensive

  Can be hard to manage and analyse all data
• Sample


  A selection of observations taken from a subset of the population which is used to find out information about the population as a whole
• Advantages of a sample

  Less time consuming

  Fewer people have to respond

  Less data than a census
• Disadvantage of a sample

  The data may not be as accurate

  The data may not be large enough to represent small sub groups of a large population
• Sampling Units


  Individual units of a population
• Sampling Frame


  A list of individually named or numbered sampling units
• Simple Random Sample


  A sample where every sampling unit has an equal chance of being chosen
• Systematic Sampling


  A method of sampling where the required elements are chosen at regular intervals from an ordered list
• Advantages of Systematic Sampling

  Simple and quick to use

  Suitable for large samples
• Disadvantages of Systematic Sampling

  A sampling frame is needed

  It can introduce bias if sampling frame is not random
• Advantages of Stratified Sampling

  Sample accuracy reflects the population structure

  guarantees proportional representation of groups within a population
• Disadvantages of Stratified Sampling

  Population must clearly classified into distinct strata
• Stratified Sampling


  A method of sampling where the population is divided into mutually exclusive strata and a random sample is taken from each
• Stratum equation


  (Number in stratum/number in population)* overall sample size
• Quota Sampling


  A method of sampling where a researcher selects a sample that reflects the characteristics of the whole population
• Advantages of Quota Sampling

  Allows a small sample to still represent the whole population

  No sampling frame required

  Quick, easy and inexpensive

  Allows for easy comparison between different groups in the population
• Disadvantages of Quota Sampling

  Not random sampling can produce bias

  Population must be divided into groups which can be costly or inaccurate

  Non-responces are recorded as such
• Opportunity Sampling


  A method of sampling where the people sampled are those who are available at the time the study is carried out and who fit the criteria you are looking for
• Advantages of Opportunity Sampling

  Easy to carry out

  Inexpensive
• Disadvantages of Opportunity Sampling

  Unlikely to provide a representative sample

  Highly dependent on individual researcher
• Quantitative Variables/Data


  Variables or data associated with numerical observations
• Qualitative Variables/Data


  Variables or data associated with non-numerical observations
• Continuous Variable


  A variable that can take any value in a given range
• Discrete Variable


  A variable that can take only specific values in a given range
• Class Boundaries


  The maximum and minimum values that belong in each class
• Midpoint


  The average of the class boundaries
• Class Width


  The difference between the upper and lower class boundaries
• Interpercentile range


  The difference between the values for 2 given percentiles.
• Cleaning the data


  The process of removing anomalies from a data set.
• bivariate data


  Data which has pairs of values for two variables
• Correlation


  A measure of the linear relationship between two variables
• regression line


  a line of best fit, y = a+bx
• mutually exclusive events


  events that have no sample points in common , P(A or B) = P(A) + P(B)
• independent events


  The outcome of one event does not affect the outcome of the second event , P(A and B) = P(A) x P(B)
• tree diagram


  A diagram used to show the total number of possible outcomes