Population vs. SamplePopulation vs. Sample

The entire group of individuals that we want The entire group of individuals that we want information about is called the information about is called the populationpopulation..

A A samplesample is a part of the population that we is a part of the population that we actually examine in order to gather actually examine in order to gather information.information.

Example: Let’s say we want to find the Example: Let’s say we want to find the average height of female students at HHS. It average height of female students at HHS. It is too much trouble to try to measure the is too much trouble to try to measure the height of each girl, so we go to 20 different height of each girl, so we go to 20 different homerooms and measure the height of 5 girls homerooms and measure the height of 5 girls in each of those homeroom.in each of those homeroom.

The population of our study is “Females at The population of our study is “Females at HHS”.HHS”.

The sample of the study is the group of 100 The sample of the study is the group of 100 girls whose height we actually measured.girls whose height we actually measured.

Sample DesignSample Design

Sample DesignSample Design is the term used to describe the is the term used to describe the method used to choose the sample from the method used to choose the sample from the population to survey.population to survey.

There are many ways to choose a sample. There are many ways to choose a sample. Some methods are more preferred than others.Some methods are more preferred than others.

Self-selected SampleSelf-selected Sample

This methods allows the sample to choose This methods allows the sample to choose themselves by responding to a general appeal themselves by responding to a general appeal (volunteering to be surveyed). (volunteering to be surveyed).

Examples of Self-selected Sample: a call-in Examples of Self-selected Sample: a call-in radio poll, an internet poll on a websiteradio poll, an internet poll on a website

Problems with Self-selected samples: bias – Problems with Self-selected samples: bias – because people with strong opinions on the because people with strong opinions on the topic (especially negative opinions) are most topic (especially negative opinions) are most likely to respond.likely to respond.

Convenience SamplingConvenience Sampling

In a convenience sample individuals are In a convenience sample individuals are chosen because they are easy to reach.chosen because they are easy to reach.

Example: People conducting a survey go to Example: People conducting a survey go to the mall and stop people who are shopping. the mall and stop people who are shopping. This is convenient for the person doing the This is convenient for the person doing the survey but does not guarantee that the sample survey but does not guarantee that the sample is representative of the population of the study.is representative of the population of the study.

Convenience sampling also involves bias on Convenience sampling also involves bias on the part of the interviewer.the part of the interviewer.

Simple Random SamplesSimple Random Samples

A random sample of size “n” individuals from A random sample of size “n” individuals from the population chosen in such a way that every the population chosen in such a way that every set of “n” individuals has an equal chance to set of “n” individuals has an equal chance to be the sample selected.be the sample selected.

Example: Putting everyone’s name in a hat Example: Putting everyone’s name in a hat and drawing 3 names to participate in the and drawing 3 names to participate in the study.study.

Systematic SampleSystematic Sample

When a rule is used to select members of the When a rule is used to select members of the population.population.

Ex. Every third person on an alphabetized listEx. Every third person on an alphabetized list

Stratified Random SampleStratified Random Sample

To select a stratified random sample, first divide To select a stratified random sample, first divide the population into groups of similar the population into groups of similar individuals, called STRATA. Then choose a individuals, called STRATA. Then choose a separate sample in each strata and combine separate sample in each strata and combine these to form the full sample. Common these to form the full sample. Common example would be separating by gender or example would be separating by gender or race first, then selecting samples from each race first, then selecting samples from each group.group.

Cluster SamplingCluster Sampling

Cluster Sampling is a sampling technique used when "natural" groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or clusters) and a sample of the groups is selected. Then the required information is collected from the elements within each selected group.

ExampleExample

A researcher studies the academic progress of middle school students in Georgia and wanted to choose a cluster sample based on geographic location. First, the researcher divides the entire population of Georgia into clusters, or counties. Next, the researcher selects either a simple random sample or a systematic random sample of those clusters (or counties). He or she chose a random sample of 32 counties and he or she wanted a final sample of 10,000 students. The researcher would then select those 10,000 middle school students from those 32 counties either through simple (or systematic random sampling). This is an example of a cluster sample.