In the last decade(2010-2020), Telecom companies made a major change in mobile recharge policy. Telecome customers was allowed to recharge based on their Internet data requirement rather than call based on. Since then, data has become a popular and common term for everyone. But the basic question is What is data in computer? What are the examples of data in computer? What does data do? From where does data comes? And how we can convert data into a piece of information? In this blog, We will discover all the answers of the given questions above. So, Let’s dive deeper in the world of data.
Note: Data is new oil in the world of Internet. Due to Internet revolution data is being generated in millions and billions every day and each piece of data is important to make any decision. Impetus of data has also grown due to emergence of Large Language models. Chat bot is being developed in almost every part of daily life such as chatbot as a medicine consultant, chatbot as a financial consultant, Chatbot as a legal consultant and many more.
- Data
The first and foremost question in the world of AI is What is data? What are the examples of data?
Data is a collection of facts and figures. It is the smallest unit of any meaningful information. For example: “Rohan reads in class 8th and his roll number is 10“.
In this statement, Name-Rohan, Class-8th, and roll number 10 are independent facts, but when I have organized these facts into a statement it has become meaningful information.
Statistics is used for data analysis. Data can be qualitative(descriptive) or quantitative(Numerical). Data is fundamental for any statistical analysis and it can be collected through various methods, such as surveys, experiments, questionnaires, or observations.
2. What are the Statistical parameters to measure Collected data
Before explaining Sampling Distribution, we must know the parameters used to measure sample data. There are various parameters such as mean, median, covariance, standard deviation, percentile, etc. These parameters are important to get insights from the collected data or the different samples of collected data.
3. Population And Sample
a. Population(N)
In statistics, Population means all the data collected from various methods for solving a pre-defined problem. let’s suppose you have to do some research on students. Then you have collected various information from 10000 students of a city. Therefore, 10000 is the size of the population. The population is denoted by ‘N’ in statistics.
b. Sample(n)
A sample is a subgroup of Population data. Let’s suppose your population size is 10000. Now you have divided population data into a group of 100. It means you have 10 samples from the given population.
4. Sampling Distribution
A sampling distribution shows how a sample statistics varies from sample to sample drawn from Population data. It helps us understand the variability and distribution of samples.
Imagine, You have a population of Students, and you want to know the average age. Instead of asking to every student, You take various random samples, each containing a few students, and calculate the mean age for each student. The distribution of these sample means is the sampling distribution of the mean.
According to the Central Limit Theorem(CLT), If the population size is sufficiently large then, the sample distributions of sample means will be normally distributed.
Sampling distributions are crucial for inferential statistics. They allow us to make generalizations on population data based on the sample data. It helps us to calculate parameters for the population and to perform hypothesis testing and other testing as well.
Types of Sampling Distribution
a. Gaussian Normal Distribution
b. Poison distribution
c. Bernauli distribution
d. Two Independent Normal Sample Distribution