Basic of Statistics
Introduction of statistics :
Statistics is the branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to a scientific, industrial, or social problem, it is conventional, to begin with a statistical population or a statistical model to be studied.
Pillers of basic statistics :
Collection :
In Statistics collection of data is collecting of data or sampling of data.
Analysis :
In Analysis Statistics we use all data analysis techniques.
Interpretation :
In Interpretation, the data is used for graphs and plotting.
Presentation :
In the presentation, the data is presented to the audience or user.
Organization :
In organization, the data is organized for further use. Such as Google
Importance of Statistics :
Statistics play a crucial role in helping us understand how to collect data effectively. They provide us with the tools and techniques necessary for gathering information most accurately and reliably possible. Before we even begin the process of collecting data, statistics guide us in selecting the best sampling methods, ensuring that our data represents the true picture of what we’re trying to study.
Scales of measurement :
There are 4 types of scales for measurement in statistics which are given below :
Nominal Scale
Ordinal Scale
Interval Scale
Ratio Scale
Nominal Scale :
In statistics, a nominal scale is the simplest level of measurement that categorizes data into distinct categories or groups without any order or ranking. It’s like labeling or naming things without any implied hierarchy.
Ordinal Scale :
In statistics, an ordinal scale is a type of measurement that categorizes data into ordered or ranked categories where the intervals between the categories are not necessarily equal. Ordinal scales allow for the ranking of data based on some criterion but do not provide information about the magnitude of differences between categories.
Interval Scale :
In statistics, an interval scale is a type of measurement that not only categorizes data into ordered categories like an ordinal scale but also has equal intervals between adjacent categories. This means that the difference between any two adjacent points on the scale is consistent and meaningful.
Ratio Scale :
In statistics, a ratio scale is the highest level of measurement that not only categorizes data into ordered categories but also has equal intervals between adjacent categories and a true zero point.
