MTHSTATS 215 Chapter 1 Quiz

Population (N)

an entire group to be studied

Sample (n)

A selection or subset of members from the population, for analysis and projection back onto the population

Descriptive Statistics

a mathematical means of organizing and summarizing information, data summarization

Inferential Statistics

the methods for drawing, and measuring the reliability of, conclusions about a people based on a sample drown from it, conclusions drawn about population from sample

Element

a single member of a population or sample (also called experimental unit)

Variable

A characteristic of the members of a population

Qualitative Variable

measures a non-numerical characteristic

Quantitative Variable

measures a characteristic that can be ranked or ordered on a numerical scale

Discrete Quantitative Variable

Can only take certain values, usually intergers

Continuous Quantitative Variable

can take on any value within an expected range

Univariate Data

only 1 variable sampled on the elements

Bivariate Data

two variables sampled

Multivariate Data

three or more variables sampled

Cross-Sectional Data

data sampled at a particular point in time across members of a population or sufficiently sized sample

Time-series Data

data sampled at multiple points in time for on or a few elements

Simple Random Sampling

every element of the population have an equal likelihood of being chosen

Stratified Random Sampling

selecting elements randomly from stratified subgroups within the population. Often done by selecting a number of elements from each subgroup that is proportional to the fraction of the overall population made up by the subgroup.

Cluster Sampling

Dividing the population into (often-naturally occurring) clusters, and then randomly sampling individual clusters and including all elements from each cluster sampled

Systematic Sampling

select the kth element randomly from the first m elements of the population, then select every mth element afterward (K+m, k+2m)

Connivence Sampling

non-random, sampling all easily reachable or accessible elements

Judgement Sampling

the experimenter decides who will be in the sample

Observational Studies

research simply observe characteristics and take measurements

Designed Experiments

researches employ treatments and controls and then observe characteristics and take measurements (often done in cause-effect studies)

Treatment

experimental condition

Response Variable

the variable that is the experimental outcome to be measured

Factor

a variable who effect on the response variable is of interest

Levels

possible values of a factor

Treatment

a combination of levels of one or more factors

Treatment Group

a group receiving a specified treatment

Control Group

a similar group not receiving any treatment or receiving baseline treatment

F(xi)

relative frequency

f(xi)

observed frequency

xi

random variable