MMW MIDTERMS Flashcards
(39 cards)
a science which deals with the collection, organization, presentation, analysis, and interpretation of data so as to give a more meaningful information.
STATISTICS
refers to the collection, organization,summary, and presentation of data
DESCRIPTIVE STATISTICS
deals with the interpretation and analysis of data where conclusion is drawn based from the subset of the population.
INFERENTIAL STATISTICS
a characteristic or attribute that can assume different values in different persons, places, or things.
VARIABLE
- data which can assume values that manifest the concept of attributes.
- aka categorical data
QUALITATIVE VARIABLES
- data are obtained from counting or measuring.
- Numerical data which represents the numerical value i.e. how much, how often, how many
QUANTITATIVE VARIABLES
- values in the variable are used to label or classify variables.
- has no order
- words, letters, and alpha numeric symbols can be used
NOMINAL
- values represent discrete and ordered units.
- follows a natural order
ORDINAL
- values tell the distances between the measurements in addition to the classification and ordering.
- do not have a true zero point
INTERVAL
- the most informative level of measurement.
- The combination of first three levels of measurements.
- order units that have the same difference
- have an absolute zero
RATIO
a way of selecting individual members or a subset of the population to make statistical inferences from them and estimate characteristics of the whole population.
SAMPLING METHODS
the entire group that you want to draw conclusions about.
POPULATION
the specific group of individuals that you will collect data from.
SAMPLE
every member of the population has a chance of being selected. It is mainly used in quantitative research
PROBABILITY SAMPLING
non-random selection based on convenience or other criteria, allowing you to easily collect data. It is often used in exploratory and qualitative research.
NON-PROBABILITY SAMPLING
- every member of the population has an equal chance of being selected.
- Your sampling frame should include the whole population.
- Two ways: lottery or fishbowl technique and table of random numbers.
SIMPLE RANDOM SAMPLE
Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.
SYSTEMATIC SAMPLING
dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Sometimes referred to as “area sampling”
CLUSTER SAMPLING
to use this sampling method, divide the population into subgroups (called strata) based on the relevant characteristic
STRATIFIED RANDOM SAMPLING
individuals who happen to be most accessible to the researcher.
CONVENIENCE SAMPLING
are always at least somewhat biased, as some people will inherently be more likely to volunteer than others.
VOLUNTARY RESPONSE SAMPLING
also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
PURPOSIVE SAMPLING
can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people.
SNOWBALL SAMPLING
- provide raw information and first-hand evidence.
- Examples include interview transcripts, statistical data, and works of art.
- gives direct access to the subject of your research
PRIMARY SOURCES