mmw

Census

this is the procedure of systematically acquiring and recording information about all members of

a given population

Sample Survey

sampling is a selection of a subset within a population, to yield some knowledge about

the population of concern

Experiment

– this is performed when there are some controlled variables (like certain treatment in

medicine) and the intention is to study their effect on other observed variables (like health of patients)

Observation study

– this is appropriate when there are no controlled variables and replication is

impossible

Data

are raw information or facts that become useful information when organized in a meaningful way

Data Management

is concerned with “looking after” and processing data

Nonprobability sampling

– is any sampling method where some elements of the population have no

chance of selection or where the probability of selection can’t be accurately determined.

Probability Sampling

– it is possible to both determine which sampling units belong to which sample

and the probability that each sample will be selected

Simple Random Sampling (SRS)

, all samples of a given size have an equal probability of being

selected and selections are independent

Systematic Sampling

– relies on dividing the target population into strata (subpopulations) of equal

size and then selecting randomly one element from the first stratum and corresponding elements

from all other strata.

Stratified Sampling

– when the population embraces a number of distinct categories, the frame

can be organized by these categories into separate “strata

confounding

– a confounding variable is an extraneous variable in a statistical model that correlates

(positively or negatively) with both the dependent variable and the independent variable

Placebo and blinding

– is an imitation pill identical to the actual treatment pill, but without

the treatment ingredients

Blocking

– is the arranging of experimental units in groups that are similar to one anothe

Completely randomized designs

– are for studying the effects of one primary factor without the

need to take other nuisance variables into account

Randomized block design

– is a collection of completely randomized experiments, each run within

one of the blocks of the total experiment

chi-square

is used to determine whether there is significant difference between the expected value

frequencies and the observed frequencies in one or more categories.

chi-square

goodness of fit test determines if a sample data matches a population

chi-square

test for independence compares two (2) variables in a contingency table to see if they

are related