sampling

• populations and samples: in any study the population is the group of individuals a researcher is interested in for examples 'babies in the Western world', 'people in the UK' or 'young people living in Bristol', at the end of the study the researcher wants to be able to make a statement about this population of people
• populations and samples: the researcher obviously can't study all the people in the population, instead the researcher selects a smaller group called the sample, ideally this sample will be representative of the population so that generalisations about the population can be made
• populations and samples: the most common sampling methods used in psychological research is in fact opportunity or volunteer sampling
• opportunity sample is when you recruit people who are most convenient or most available e.g. people walking by you in the street or students at your school
• stratified sample are subgroups (or strata) within a population are identified (e.g. boys and girls or age groups 10-12 years, 13-15 etc) participants are obtained from each of the strata in proportion to their occurrence in the population, selection from the strata is done using a random technique
• systematic sample is when you use a predetermined system to select participants such as selecting every nth person from a phonebook (where n = any number) the numerical interval is applied consistently
• volunteer sample is an advertise in a newspaper or on a noticeboard or on the internet
• opportunity S: the easiest method because you just use the 1st suitable participants you can find which means it takes less time to locate your sample than if using one of the other techniques
• random S: unbiased all members of the target population have an equal chance of selection
• stratified S: likely to be more representative than other methods because there is a proportional and randomly selected representation of subgroups
• systematic S: unbiased as participants are selected using an objective system
• volunteer S: gives access to a variety of participants (e.g. all the people who read a particular newspaper) which may make the sample more representative and less biased
• opportunity L: inevitably biased because the sample is drawn from a small part of the population e.g. if you selected your sample from people walking around a centre of a town on a Monday morning then it would be unlikely to include professional people (because they are at work) or people from rural areas
• random L: need to have a list of all the members of the population and then contact all those selected, which may take some time
• stratified L: very time consuming to identify subgroups and then randomly select participants and contact them
• systematic L: not tryly unbiased/random unless you select a number using a random method and start w/ this person and then select every nth person
• volunteer L: sample is biased in other ways because participants are likely to be more highly motivated and/or w/ extra time on their hands they might be more highly motivated to be helpful or more broke and needing the money offered for participation this results in a volunteer bias
• random techniques: people tend to use the word 'random' to mean 'whatever comes into my head'. in science the word random has a very specific meaning, it means that each item in a population has an equal chance of being selected
• random techniques: there are various random techniques that are used to obtain a random sample (or also to achieve random allocation of participants to groups)
• the lottery method: the easiest way to obtain a random selection is to draw numbers or names 'out of a hat', this is sometimes called the lottery method
• the lottery method: 3 important steps = 1. obtain a list of all the people in the population, this may simply be the names of all the people in your school
• the lottery method: 2. put all the names in a lottery barrel or hat
• the lottery method: 3. select the number of names required
• the lottery method: if a researcher is using this method for random allocation of participants to groups then they might put the 1st 10 names drawn in a group A and the second 10 names in group B
• random number table: an alternative random technique is to use a printed table of random numbers, also is 3 steps
• random number table: 1. this time every member if the population is given a number
• random number table: 2. the starting position in the table is determined blindly by placing your finger anywhere
• random number table: 3. if your population is less than 100 you only need 2 digit numbers so read the table 2 digits at a time
• random number generators: calculators have functions that generate random numbers as do computers and apps on phones
• random number generators: 1. number every member of the population
• random number generators: using e.g. Microsoft Excel type = RAND(100) to get a random number between 1 and 100
• bias: bias means 'distorted' in some way, you will come across also of biases in psychological research: experimenter bias, interviewer bias, observer bias, social desirability and 2 that relate to sampling = sample bias and volunteer bias
• bias: a sample bias describes the fact that even though all sampling methods aim to produce a representative sample they are inevitably biased or distorted e.g. an opportunity sample differs from the population because it only represents one particular group of people - the people who happen to be easily available to the researcher
• bias: a volunteer bias describes the fact that people who volunteer to take part in research are likely to be different to other members of the population and this distorts or biases the data they produce