data management Flashcards
(32 cards)
is a process by which information is acquired and
processed to ensure the accessibility and reliability of
the data for its users
Data Management
is a science which deals with the collection,
organization,presentation, analysis, and interpretation
of data so as to give a more meaningful information.
Statistics
One of the most important tool in processing and
managing such information is statistics
Data Management
subdivided into two branches, namely: descriptive
statistics and inferential statistics
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
Examples are hypothesis testing
and regression analysis
Inferential Statistics
Examples are the measures of
location, measures of
variability, skewness and
kurtosis
Descriptive Statistics
Is a characteristic or attribute that can assume
different values in different persons, places, or things.
VARIABLE
includes age, race, gender, intelligence, personality
type, attitudes, ethnic group or patients, height,
weight, heart rate, marital status, eye color, etc.
VARIABLE
data which can assume values that
manifest the concept of attributes.
Qualitative Variables
data are obtained from counting or
measuring.
Quantitative Variables
are sometimes called categorical
data.
Qualitative Variables
Numerical data which represents the
numerical value i.e. how much, how often,
how many
Quantitative Variables
Numerical data gives information about the
quantities of a specific thing e.g. height,
length, weight, test score, and so on.
Quantitative Variables
this type of data can’t be
measured but it can be counted.
e.g. number of students in a
class
Discrete Variables
e.g. person’s gender, home town,
birthdate, post code, marital status,
eye color, etc.
Qualitative Variables
e.g. variables found in surveys, finance, economics,
questionnaires, and so on.
ordinal
Continuous data has an infinite
number of probable values that can
be selected within a given range.
Continuous Variables
contains only a finite number of
possible values.
Discrete Variables
values in the variable are used to label or classify variables.
_______ data has no order.
Nominal
This type of data can’t be counted
but it can be measured. e.g.
temperature range
Continuous Variables
words, letters and alpha numeric symbols can be used.
Nominal
Ordinal data follows a
natural order