A numerical summary of population


A numerical summary of sample;
A science of collecting, organizing and analyzing the data

Steps of Statistic; Identification

Population-A group of men or objects to be studied;
Individual-A singular man or object to be studied

Steps of Statistic; Collection

Sample-A representative subset of the population

Steps of Statistic; Organization

Descriptive Statistic-Arranged & collected data

Steps of Statistic; Conclusion

Inferential Statistic- Applying the result to the real world
* Due to its nature, one cannot be 100% sure of the validity of statistic application (AKA samping error)


Info collected for conclusion;
An observed value(coule be both qualitative and quantitative)

Qualitative Variable

Attribute characteristics or classification; Adding or subtracting doesn't have meaning.

Quantitative Variable

Gives numerical measures, subtract and addition will have significant impact.

Discrete variable

Countable and finite. Concrete, part of quantitative variable

Continuous variable

Infinite # of possible values; cannot be counted and needs to be measured.
ie) Height, time


Characteristics of individual

Explanatory variable

The cause or treatment, independent. Explains the outcome of the sample

Response variable

The ourcome or result, dependent. Impacted by explanatory variable

Designed Experiment

When researchers deliberately control/manipulate the explanatory variable to determine its impact. Casuation achieved

Observational study

When reserachers simply observe. No messing with the treatment. Cannot establish casuation, only association is possible.

Lurking variable

Third variable that influecnes other variables and consequently the response variable. Often hidden.


State where an experiment is affected by lurking variable; the outcome in most cases is uncredible.


The complete list containing the individuals in the population. Takes lot of time and effort to make it, therefore done seldomly. (Some still argues there's a gaphole, as in reality with citizens government has no way of measuring the homeless population)


AKA simple random sampling. Need randomly selected n from N. Onces chose, men cannot be RE-SELECTED. If each n has equal chance of occruing, SRS is achieved.

Stratified Sampling

Separates the population into groups called strata where each belongers have sth in similarity. Then randomly select few representatives from each stratum. Gurantees the representation from one end to another.

Systematic sampling

Select every kth individual from the population by applying the formula k=N/n. Get a starting point between 1~k, and nail every person that comes up after kth turn. Does NOT NEED FRAME, therefore ideal when one only knows N.

Cluster sampling

Select some natrually-occuring groups within the cluster of population, and sample everyone in that selected group. Except then you can miss out the entire facade of the population, or worse, your intended target.

Convience sample

When one's lazy enough, she will go where sample is not collected based on randomness but from voluntary response, like when men decides to reply to the survey. Population tends to be biased.