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Chapter 5 - Organization of Data - Coggle Diagram
Chapter 5 - Organization of Data
Bias and Different Types of Bias
Occurs when there is a prejudice for or against an idea or response
Biased samples can result from problems with either the sampling technique or the data collection method
Example: A survey question that asks whether you agree that the government should continue to waste money is biased because it leads people to change their opinion towards government spending
Types of Samples
Stratified
Divide the sample into groups with the same proportions as those groups in the population
Time- and cost-efficient to conduct
Cluster
Divide the population into groups, randomly choose a number of the groups and sample each member of the chosen group
Systematic
Put the population in an ordered list and choose people at regular intervals
Multistage
Divide the population into a heirarchy and choose a random sample at each level
Simple Random
Randomly choose a specific number of people
Examples: Stratified samples and systematic samples
Voluntary
Allow participants to choose whether or not to participate
Often the only people who respond are either heavily in favour or heavily against what the survey is about
Convienence
Choose individuals from the population who are easy to access
Can yield unreliable results since it inadvertently omits large portions of the population
Often very inexpensive to conduct
Population Definition
All the individuals in a group that is being studied
Observational Study
where researchers observe the effect of a risk factor, diagnostic test, treatment or other intervention without trying to change who is or isn't exposed to it.
Cohort studies and case control studies are two types of observational studies
Sample Variability
Shows how samples are different from each other
The more similar the samples are to each other, the lower the variablitity and the more accurately the samples represent the populations
Groups
Treatment Groups
The participants in an experiment who receive the specific treatment being measured
Control Group
The participants in an experiment who do not receive the specific treatment being measured
Compared to the treatment group
Sample
A group of items ot people selected from the population
Types of Data
Micro Data
An individual set of data about a single respondent
Ordinal Data
Qualitative data that can be ranked
Examples: poor, fair, good, very good
Nominal Data
Qualitative data that cannot be ranked
Examples: blue eyes, green eyes, brown eyes
Aggregate Data
Data that are combined or summarized in such a way that the individual micro data can no longer be determined
Categorial Data
Data that can be sorted into distinct groups or categories
Numerical Data
Data in the form of any number
Sources of Data
Primary Source Data
Data that have been collected directly by the researcher and have not been manipulated or summarized
Secondary Source Data
Data used by someone other than those who actually collected them