Definition of Variable, Measurement Scale, Qualitative and Quantitative Data

Variable and Data Definitions

The characteristics of an individual or object that can be observed and which are different from other individuals in a population are called variables or variables. While the observations themselves are specific values ​​of a variable. Generally the variable is represented by the Latin letters, from A to Z, although generally the last three are X, Y, Z. If X has ten observations, the observations are recorded with X1, X2, X3, ... X10. Because the variables are closely related to the values ​​of observations or data, where data is a collection of information obtained from an observation, it can be a number, symbol or nature.
Information or data is always needed in every decision making process. However, not all data provides benefits in decision making. If the data obtained is not feasible or flawed because of bias, unclear, or because of other errors, then there is no one method to fix it.
Therefore, good and correct data collection methods need to get serious attention, so that the data obtained provides maximum benefits.

Method of Obtaining Data

There are several methods that can be used to get the data needed, namely by:
  1. Find data that has been published by certain sources, whether governments, companies or individuals.
  2. Design an experiment.
  3. Conduct a survey
Basically, data obtained using these three methods can be grouped into two types of data, namely two qualitative and quantitative data.

Types of Data by Nature (Qualitative and Quantitative)

Qualitative data is data that is stated in the form of categories or data that cannot be measured with certainty. For example data about type, sex, fabric color and type of work.
Qualitative data can be grouped into two types of data, namely nominal data and ordinal data.
  1. Nominal data is qualitative data that is grouped into one category from several categories created. For example regarding gender (male and female) is an example of nominal data.
  2. Ordinal Data is qualitative data that is grouped into a sequence or ranking. For example education level data (elementary, junior high, high school, university).

Quantitative Data is numerical or can be measured with certainty, for example about agricultural output, income per capita of the American population and body weight. Furthermore this quantitative data is divided into two namely interval and ratio data.
  1. Interval data are quantitative data that have the same and fixed distance between one point and another on the measurement scale. For example the size of the air temperature expressed in units of centigrade.
  2. Ratio data is quantitative data that has a zero point and a ratio between two significant data values. For example the price stated in dollars. Items that cost $ 20 are cheaper than items that cost $ 200.

Quantitative data can be further grouped into discrete and continuous data.
  1. Discrete data is data that is collected is an integer. Discrete data can only take values ​​at a certain point in an interval or interval, so that there is always a distance or gap between the values.
  2. Continuous data are continuous counting numbers usually obtained as a result of measurements and their values ​​can take any value in a certain interval. For example, to measure plant height, body height and others.
Examples of data in various measurement scales:

Scale of Measurement
Qualitative Data
Category
Nominal Data

Gender
Currency
Male
Women
Font
Back
Ordinal Data

Final Score
A
C
B
D

E


Class Rank
1
4
2
5
3
6
Interval Scale
Temperature
Celcius, Fahrenheit, Reamur, Kalvein
Scale ratio
Height
Weight
Age
Cm, Meters, Inchi, Kg, Pound, Year, Month, Day


Types of Data Base On Source

  1. Internal data is data of an organization that describes the state of the organization. For example the number of employees, capital, production of an insurance company or others.
  2. External data is data obtained from outside an organization that can describe the factors that might affect the work results of an organization. For example, the purchasing power of American society influences the sales results of Veeam software.

Data Types Based on How to Get It

  1. Primary Data is data collected by individuals / organizations directly from the object under study and for the benefit of the relevant study which can be in the form of interviews, observations.
  2. Secondary Data is data obtained / collected and put together by previous studies or published by various other agencies. Usually the indirect sources are documentation data and official archives.

Data Types Based on Time of Collection

  1. Cross Section Data is data collected at a certain time to describe the circumstances and activities at that time. For example, research data using a questionnaire.
  2. Periodic Data (Timer Series Data) is data collected from time to time to see the development of an event / activity during that period. For example, the development of money supply, the price of 9 kinds of basic commodities.

That is all about the measurement scale, the definition of variables and data and the type of data. May be useful.

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