Unit 2 Quiz Review Flashcards
(30 cards)
Inference
A conclusion about the population based on sample data.
Population vs Sample
The group being studied is called the population a selection of individuals taken from the population is the sample.
Cross-Sectional study
A study that considered individuals from different groups at the same time.
Longitudinal Study
A study of a single group (Sample) over a long time to recognize change over time.
Time series data
Data that have accumulated over a long time.
Quantitative
Numerical data
Qualitative
Non numerical data
Discrete data
Data that is in integral values (Easily countable).
Continuous Data
Data resulting from the measure of quantity (Decimals).
Simple random sampling
All selections must be equally likely
All combinations of selections must be equally likely
Everyone has a chance
Systematic random sampling
Fixed percent of population
Random starting point (individual household) they select every nth individual
Stratified random sampling
Divided into groups called strata (geographic area, age)
A random sample of strata is take
Cluster random sampling
Population organized into groups (schools , communities)
A random group is chosen and surveyed (All of them surveyed)
Multi-staged random sampling
A population out into groups
A random sample of groups is chosen then take info
50% 50% example
Destructive sampling
Samples that can’t be reintroduced into the population
Example (lightbulb test)
To test products
Product is destroyed
Primary data
Data that is collected on your own (Survey)
Secondary data
Data collected from another source
Open ended questions
Respondents reply in their own words
Closed ended questions
Respondents are given a limited number of responses from which they choose
Good questions
Relevant
Simple
Readable
Specific
Good questions should avoid
Negative Jargon Abbreviations Insensitivity Leading respondent
Bias
An unintended influence on data-gathering method.(Unfair)
Sampling bias
When the chosen sample does not accurately represent the population.
Non-response bias
When the results are influenced because surveyed are not returned.
Or the answer you provide is invalid.