Statistics

• What is raw data?

  Unprocessed data that has just been collected and needs to be ordered, grouped, rounded, cleaned.
• What is qualitative data?

  Non-numerical, descriptive data such as eye/hair colour or gender. Often subjective so usually more difficult to analyse.
• What is quantitative data?

  Numerical data that can be measured with numbers. Easier to analyse than qualitative data. Example, height, weights, marks in an exam etc.
• What is discrete data?

  Data that only takes particular values (not necessarily whole numbers) such as shoe size or number of people.
• What is continuous data?

  Data that can take any value e.g. height, weight.
• What is categorical data?

  Data that can be sorted into non-overlapping categories such as gender. Used for qualitative data so that it can be more easily processed.
• What is ordinal data?

  Quantitative data that can be given an order or ranked on a rating scale, e.g. marks in an exam.
• What is bivariate data?

  Data that involves measuring 2 variables. Can be qualitative or quantitative, grouped or ungrouped. Usually used with scatter diagrams where the two axes represent the two different variables.
• What is multivariate data?

  Data that is made up of more than 2 variables e.g. comparing height, weight, age and shoe size together.
• What does grouping data mean?

  Grouping data using tables makes it easier to spot patterns in the data and quickly see how the data is distributed.
• What are the pros of grouping data?

  Makes the data easy to read and understand, easy to spot patterns and compare data.
• What are the cons of grouping data?

  Loses accuracy of data as you no longer know exact data values. Calculations made from these will only be an estimate e.g. mean.
• What is primary data?

  Data that you have collected yourself, or someone has collected on your behalf.
• What is secondary data?

  Data that has already been collected.
• What is a population in the context of an investigation?

  Everyone or everything that could be involved in the investigation.
• What is a census?

  A survey of the entire population.
• What is a sample?

  A smaller number from the population that you actually survey. The data obtained from the sample is then used to make conclusions about the whole population.
• What is a sampling frame?

  A list of all the members of the population. This is where you will choose the sample from.
• What is a sampling unit?

  The people that are to be sampled e.g. students in a school.
• What is a biased sample?

  A sample that does not represent the population fairly. Example, if surveying students at a mixed school and the sample only contains girls.
• What is a random sample?

  A sample where every item/person in the population has an equal chance of being selected.
• What are some random sampling techniques?

  Pick numbers/names out of a hat, using a random number table, using the random number generator function on a calculator or computer.
• What are the advantages of random sampling?

  Sample is representative as every member of the population has an equal chance of being selected. It's unbiased.
• What are the disadvantages of random sampling?

  Need a full list of population (not always easily obtainable), not always convenient as it can be expensive and time consuming, needs a large sample size.
• What is a stratified sample?

  A sample where the size of each strata (group) in the sample is in proportion to the sizes of strata in the population.
• What is the method for stratified sampling?

  Split the population into groups, use the formula 𝒔𝒕𝒓𝒂𝒕𝒊𝒇𝒊𝒆𝒅 𝒔𝒂𝒎𝒑𝒍𝒆 = 𝒔𝒕𝒓𝒂𝒕𝒂/𝒕𝒐𝒕𝒂𝒍 × 𝒔𝒂𝒎𝒑𝒍𝒆 𝒔𝒊𝒛𝒆 to calculate sample size for each group, and use random sampling to select members from each strata/group.
• What are the advantages of stratified sampling?

  Sample is in proportion to population, so sample represents the population fairly. Best used for populations with groups of unequal sizes.
• What are the disadvantages of stratified sampling?

  Time consuming.
• What is systematic sampling?

  A method of choosing items in the population at regular intervals.
• What is the method for systematic sampling?

  Divide your population size by sample size to calculate the intervals, use random sampling to generate a number between 1 and the answer to your calculation from above to choose a starting point, select every nth item after the starting point until you obtain your sample size.
• What are the advantages of systematic sampling?

  Population is evenly sampled, can be carried out by a machine, sample is easy to select.
• What are the disadvantages of systematic sampling?

  Not strictly a random sample as some member of the population cannot be chosen.
• What is cluster sampling?

  A method where the population is divided into natural groups (clusters), groups are chosen at random and every member of groups are sampled.
• What are the advantages of cluster sampling?

  Economically efficient - less resources required. Can be representative if lots of small clusters are sampled.
• What are the disadvantages of cluster sampling?

  Clusters may not be representative of the population and may lead to a biased sample. High sampling error.
• What is quota sampling?

  A method where population is grouped by characteristics and a fixed amount is sampled from every group.
• What is the method for quota sampling?

  Group population by characteristics e.g. gender and age, select quota (amount) for each group e.g. 30 men under 25, 40 women over 30 etc., obtain sample by finding members of each group until quota is reached.
• What are the advantages of quota sampling?

  Quick to use, cheap, do not need sample frame or full list of the population.
• What are the disadvantages of quota sampling?

  Not random - biased as interviewer is choosing who will be in the sample so every member of the population does not have an equal chance of being selected.
• What is opportunity sampling?

  Using the people/items that are available at the time.