Sampling and bias

Sampling and bias

1. population

   • population = a whole group you're interested in
   • sample = smaller group from the population
     • your sample must fairly represent your population
   • for your sample to be representative, it needs to be a random sample ( each member of the population has an equal change of being in it ), and it must be big enough for the size of the population, the bigger the sample, the more reliable

2. to select a random sample :

   • assign a number to every member of a population
     • create a list of random numbers, by using a calculator or computer
       • match the random numbers to members of the population

3. a biased sample is one that doesn't properly represent the whole population

   • you spot bias by considering :
     • when, where, and how the sample was taken
     • how many members were in the sample
   • if certain groups are excluded, the sample isnt random