sampling

• Sampling: 

  -              It is unlikely that a whole population can be studied and so a sample of that population needs to be used. 

  -              The aim of a sampling method is to select a representative sample 

  -              Sampling basis occurs when a someone may not who representative 

  -              E.g. attuites towards non-smoking policy gathers from participants recruited from an outside office smoking area. 
• Sampling technique &Description 

  • Random sample

  Every member of the target population has an equal chance of being selected for the sample

  • Stratified sample 

  Participants are selected from different subgroups in the target population in proportion to the subgroup’s frequency in the population. 

  • Volunteer sample

  A sample of participants produced by asking for people willing to take part 

  • Opportunity sample

  A sample of participants produced by selecting people who are most easily available at the time of the study. 
• Sampling technique &example 

  • Random sample

  For example, picking names out of a hat or using a random number generator 

  • Stratified sample 

  Subgroups such as age groups are identified and the number in each subgroup in the target population is identified. If 30% of the world’s population are age 10-12 years old, then 30% of the sample should be 10-12 years old. 

  • Volunteer sample

  Advertise in a newspaper or on a noticeboard

  • Opportunity sample

  As people walking by in the street 
• Sampling technique &strengths

  • Random sample

  Unbiased, all members of the target population have an equal chance of being selected 

  • Stratified sample 

  The most representative of all the techniques as subgroups are represented in proportion 

  • Volunteer sample

  A convenient way to find willing participants. They would be willing to commit to the research and less likely to drop out. 

  • opportunity sample

  Most convenient techniques as it takes little preparation. 
• Sampling technique &weaknesses

  • Random sample

  Takes time and effort as you need to gain a list of the whole population. Not everyone identified will want to take part, so the technique is not truly random. 

  • Stratified sample 

  lengthy process-may end in participants not wanting to take part. decision on which subgroups to use= biased

  • Volunteer sample

  sample=highly motivated and have extra time(volunteer bias). they try to guess aim of the study and respond to demand characteristics

  • Opportunity sample

  Sample-not representative. Those agree to take part may be subject to demand characteristics