Surveys and Questionnaires

Population versus Sample

Population  All individuals or items that belong to a group being studied

Population versus Sample Population  All individuals or items that belong to a group being studied  The population when studying the coffee purchasing habits of students at South Carleton is all of the students at South Carleton

Population versus Sample Sample  A group of individuals or items that are representative of the population from which they are taken

Population versus Sample Sample  A group of individuals or items that are representative of the population from which they are taken  Sampling 100 students at South Carleton to determine their coffee purchasing habits

Population versus Sample  Why would you want to avoid surveying an entire population?

Population versus Sample  Why would you want to avoid surveying an entire population? 1.A sample can be extremely accurate 2.It is extremely difficult to survey an entire population

Census  The collection of data from every individual in a population

Representative Sample  The sample is typical of the entire population  Conducting a survey of Canadians would involve surveying people from all parts of the country with a higher number of people from larger cities such as Toronto or Vancouver

Representative Sample  Samples that are not representative of the population can lead to biased results that may lead to invalid results.  As an example, surveying only people from Atlantic Canada would not be reflective of all Canadians

Random Sample  Every member of the population has an equal chance of being surveyed.  A non-random technique may not lead to a representative sample but may be more appropriate in some cases.

Sampling Techniques Random  Simple random sampling  Stratified sampling  Cluster sampling  Systematic sampling Non-random  Convenience sampling  Judgement sampling  Voluntary sampling

Random Techniques Simple random sampling  Sampling in which individuals are chosen randomly from the entire population

Random Techniques Stratified Sampling  Sampling in which the population is placed in groups and a sample from each group is randomly selected.

Random Techniques Stratified Sampling  Sampling in which the population is placed in groups and a sample from each group is randomly selected.  Example, surveying a number of students from each grade at South Carleton where the grades 9’s are group, 10’s another, etc.

Randon Techniques Cluster Sampling  The population is organized into representative groups and random groups are chosen to be surveyed.

Randon Techniques Cluster Sampling  The population is organized into representative groups and random groups are chosen to be surveyed.  Example: selecting certain tables at lunch hour in the cafeteria at South Carleton.

Randon Techniques Systematic Sampling  Sampling in which every n th individual is selected.

Randon Techniques Systematic Sampling  Sampling in which every n th individual is selected.  Example: Sampling every 11 th person, alphabetically.

Non-randon Techniques Convenience Sample  Sampling in which those individuals who are surveyed are surveyed because they are “convenient”.

Non-randon Techniques Convenience Sample  Sampling in which those individuals who are surveyed are surveyed because they are “convenient”.  Example: Surveying individuals attending a Senators game regarding their opinion on a new third jersey.

Non-randon Techniques Judgement Sampling  Sampling in which the person conducting the survey uses their judgement to create a representative sample.

Non-randon Techniques Voluntary Sample  Sampling in the individuals who are being sampled are participating because they have volunteered.

Non-randon Techniques Voluntary Sample  Sampling in the individuals who are being sampled are participating because they have volunteered.  Example: American Idol

Bias  Biased questions restrict people’s choices or influences them to answer in a particular way.  Example: Mayor Jim Watson has done an excellent job of keeping property tax increases to a minimum. If he chose to run again in the next election, would you vote for him?

Bias  Example: Mayor Jim Watson has done an excellent job of keeping property tax increases to a minimum. If he chose to run again in the next election, would you vote for him?  Why might this question create a bias?

Survey Techniques If you want people to answer honestly you must: 1.Ensure the integrity of the survey; 2.Ensure anonymity; 3.Remain focused on the survey topic.