# Basics of Statistics — Part 2

This is the 2nd part of the series of Understanding Statistics.

Vital terms in Statistics

Population: As the term is self-explanatory, population is nothing but the universe of possible data.

· Example: People who visited a particular website.

Parameter: A numerical value associated with the population.

· Example: Average amount of time people spent on website.

Sample: A selection of observations from a population.

· Example: People who visited the website on a particular time of the day.

Statistic: A numerical value associated with an observed value.

· Example: Average amount of time people spent on a website on a particular day.

Vital terms of Statistics

In the previous article we’ve touched up on what data , however we haven’t understood how we get the data.

Lets look in to that for a bit .

DATA SOURCES

There are basically 2 Types of data Sources

1. Primary Data

2. Secondary Data

Primary Data: Data that is being collected regularly (Data collected on daily basis).

Secondary Data: Data which is already been collected and stored, which might be for a set of days.

Let’s touch a bit on the types of Data sets.

What are Data sets?

data set is a collection of numbers or values that relate to a particular subject.

Example: The test scores of each student in a particular class is a data set.

Types of Data Sets:

Data sets are broadly classified in to 3 groups namely:

· *Record Data: *Most basic form of which has no relation between records or data fields and every data object has same set of attributes.

Examples*: *Transaction data, data matrix.

## 50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

## Statistics for Data Science

Statistics for Data Science and Machine Learning Engineer. I’ll try to teach you just enough to be dangerous, and pique your interest just enough that you’ll go off and learn more.

## Data Science With Python Training | Python Data Science Course | Intellipaat

🔵 Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...

## Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

## Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...