13 terms in 3
3.1: Population
The entire collection of items, people, or observations of interest in a statistical investigation. A population can be
Sampling Methods
3.1: Population
A complete count of the entire population where data is collected from every individual member. Examples include the nat
Sampling Methods
3.1: Population
A subset of the population selected for investigation. The sample is studied to make inferences about the population. A
Sampling Methods
3.1: Population
When all outcomes in a sample space are equally likely, the probability of each outcome is 1/n where n is the total numb
Sampling Methods
3.2: Random Sampling
A sampling method where every member of the population has an equal probability of selection, and selections are indepen
Sampling Methods
3.2: Random Sampling
A sampling method where the population is divided into k equal intervals and every kth member is selected after a random
Sampling Methods
3.2: Random Sampling
A sampling method that divides the population into non-overlapping subgroups (strata) based on shared characteristics, t
Sampling Methods
3.2: Random Sampling
A sampling method that divides the population into naturally occurring clusters, randomly selects some clusters, and inc
Sampling Methods
3.2: Random Sampling
A non-random sampling method where the population is divided into strata and the researcher selects members from each st
Sampling Methods
3.2: Random Sampling
A convenience sampling method where the sample consists of individuals who are readily available and accessible, with no
Sampling Methods
3.3: Judgmental Sampling
Judgmental (purposive) sampling relies on the researcher's judgment to select a sample. Items are chosen because they're
Sampling Methods
3.3: Judgmental Sampling
In stratified sampling, strata are non-overlapping groups within the population, each defined by a characteristic (age,
Sampling Methods