Getting Started With Statistics

Why Statistics?

Business Statistics is the science of good decision making which can be used in multiple disciplines and work areas. In today’s world data has become an essential part for a company’s growth. There are tons of valuable data that can be processed into meaningful insights. There are also large data storage capacity that can be processed using cloud and parallel computing.

What are the Methods In Statistics?

There are three methods in Statistics:-

• Classification- This method is used when data is classified into different buckets or units
• Pattern Recognition- This method is used for certain shapes, data forms that appear in common. Eg: Histogram, Boxplot, Scatter plot etc. Used to separate pattern from noise
• Association- This method is used for correlation and seeing relationship between variables

What are the Four Pillars of Statistics?

There are basically two types- Descriptive and Inferential, Inferential is further divided into Diagnostic, Predictive & Prescriptive

• Descriptive Statistics- Statistics which defines the story and as is picture of the data
• Diagnostic Statistics- Statistics which define why the numbers and data looks like this
• Predictive Statistics- Statistics which defines what the data will look like in the future
• Prescriptive Statistics- Statistics which defines what should be recommended after analysis

 What are the Vital Terms Used In Statistics?

Population- It is a universe of possible data for a specified object which is not observed. Eg: People who have or will visit a website

Parameter- It is a numerical value associated with a population which is not observed. Eg: Average amount of time people spend on a website

Sample- It is a selection of observation from a population which is observed. Eg: People who have visited a website on a specific day

Statistic- It is a numerical value associated with an observed value. Eg: Average amount of time people spend on a website on a specific day.

 

What are the Data Sources?

There are majorly two sources:-

• Primary Data- Data that is collected continuously which is fresh
• Secondary Data- Data which is already there, archived or published

What are the types of Data?

  

Qualitative Data- Data which cannot be measured, can be used using some label or ASCII codes. Eg: Gender, Religion, Place of Birth. It is of four types:-

• Nominal- Names of things. Eg: Hair color, zip codes
• Binary- Is Nominal but only two states(0 and 1) which is further divided into Symmetric Binary(both outcomes equally important, eg: Gender) and Asymmetric Binary(both outcomes not equally important, eg: Medical Test
• Ordinal- Values have meaningful order but magnitude between successive values is not known. Eg: Grades, Army Rankings

Quantitative Data- Data that can be measured and which is further divided into Discrete and Continuous

• Discrete- Data that can take certain values, discontinuities. Works in a counting process. Eg: No of rooms in a hotel
• Interval- Data that is measured on a scale of equal sized units, values that have order. Eg: Temperature, Calendar Date
• Ratio- Data that has an inherent 0 point, speak of values as being an order of magnitude. Eg: Temperature in K, Monetary Quantities

What are the types of Data Sets?

There are 4 types of data sets:-

• Record- Eg: Matrix, Transaction Data, Relational Records, Cross tabs
• Graph Network- Eg: Molecular Structures
• Ordered- Eg: Video data, Time Series
• Spatial, Image & Multimedia

 Summary!

 So far we know what are the different important terms used in statistics and how statistics is classified into further broader concepts. This document can serve as a beginners guide for anyone who wants to learn about statistics and analytics