Population Interest
Entire collection of individuals
Sample
Subset of population, selected for study in some prescribed manner
Parameter
A numerical summary that describes a characteristic of the population
Statistic
Numeral summary that describes a characteristic of the sample (known once the data are observed)
Subjects
People on whom we experiment
- entire set of subjects is the population
- set of subjects you observe is your sample
Respondents
Individuals who answer a survey
Experimental units
Animals, plants, and inanimate objects
Variables
characteristics recorded about each individual
Categorical(Qualitative) VS Numerical(Quantitative) Variable
Categorical - places a subject into one of several groups or categories
-Nominal: no order
-Ordinal: levels have some order
Numerical - measures a numerical quantity or amount in each subject
-Discrete; can take on any value in a given interval
-Continuous: can take on any value in a given interval
Population parameter
Numerical Summary of population
Census
Special sample that includes everyone and “samples” the entire population
-too expensive
-undercoverage
-too time-consuming
Population Inference
results from the sample can be generalized to a n entire population (as estimates)
Casual (cause and effect) Inference
The difference in the responses is caused by the difference in treatments when comparing the results from two treatment groups
Simple Random Samples
- SRS of size n: each sample of size n in the population hast the same chance of being selected
- Samples drawn at random generally differ from one another which leads to different values for variables we measure
-sampling variability is sample-to-sample differences
Stratified Random Sampling
-Population is first divided into different homogenous groups, called strata then take an SrS within each stratum before the results are combined
-Reduce bias and variability of results
Systematic Random Sampling
-Start from a randomly selected individual, then sample every kth person
-example: to estimate the proportion of individuals that support federal party X in the area, set up a booth and ask every 50th person your question
Cluster Random Sampling
Splitting the population into similar groups (or clusters), select one or a few clusters at random and perform a census within each of them
-Not the same as stratified sampling because this only takes a few groups, meanwhile stratified samples all groups.
Selection bias (Undercoverage)
Some portion of the population is not sampled at all or has a smaller representation in the sample than it has int he population
Response Bias
Refers to anything in the surgery design that influences responses
- Respondents may lie, especially if asked about illegal or unpopular behaviour
Voluntary Response Bias
Occurs when individuals can choose on their own whether to participate in the sample
Non-Response Bias
When a large proportion of those sampled faint o respond
Lurking variables
Related to both group membership and response.
Observational Study
Investigator observes individuals and measures variables of interest but does NOTE attempt to influence responses
-Valuable for discovering trends and possible relationships
-Retrospective : Individuals are sampled and information is collected about their past
-Prospective : individuals are followed over time and data about them is collected as their characteristics or circumstances change.
Observational Study
Investigator observes individuals and measures variables of interest but does NOTE attempt to influence responses
-Valuable for discovering trends and possible relationships
-Retrospective : Individuals are sampled and information is collected about their past
-Prospective : individuals are followed over time and data about them is collected as their characteristics or circumstances change.
