Numerical data is numbers. Non-numerical data is anything else.
The range is the difference between the greatest and least numbers.
The mode.
A statistic is a number or a fraction or any form of numerical data. A fact is an accepted theory or idea that can be proven.
Qualitative and quantitative data are both 2 important types of data. Qualitative data is data based on observation and description. An easy way to remember this, Qualitative ---> QUALity. Examples of qualitative data are when you record colors, smells, textures, etc... Quantitative data is based on numerical values. An easy way to remember this, Quantitative ---> QUANTity. An example of quantitative data are any type of numerical values.
A number that describes numerical data is a Statistic.
The range is the difference between the greatest and least numbers.
The mode.
Statistics as a numerical facts are data collected and organised numerically, whilst Statistic as a discipline or field of study which involves collecting, organizing, summarizing and presenting of data.
A statistic is a number or a fraction or any form of numerical data. A fact is an accepted theory or idea that can be proven.
Basically categorical variable yield data in the categories e.g sex (male, female), modes of transport (Bus, railway, etc) and numerical variables yield data in numerical form e.g. age (0-100), number of accident on a certain highway (0,1,2,..).
Numerical data is quantitative research
Numerical data is data measured or identified on a numerical scale. Numerical can be analyzed using statistical methods, and results can be displayed using tables, charts, histograms, and graphs.
Numerical data are organized by a graph.
Qualitative and quantitative data are both 2 important types of data. Qualitative data is data based on observation and description. An easy way to remember this, Qualitative ---> QUALity. Examples of qualitative data are when you record colors, smells, textures, etc... Quantitative data is based on numerical values. An easy way to remember this, Quantitative ---> QUANTity. An example of quantitative data are any type of numerical values.
difference between Data Mining and OLAP
A number that describes numerical data is a Statistic.
Understanding and interpret numerical data