Introduction

There is often a question raised

• Why do we need to learn statistics and probability? 

• What roles do probability and statistics play in the data science field?

Let us make the thing logical and understandable about what is the significance of it? 

What is Central Limit Theorem? 

It is a theorem that plays a very important role in Statistics. It states that the distribution of samples will be normally distributed if you have the mean (μ) and standard deviation (σ) of the population and huge randomized samples are chosen from the population with replacement. 

          

                                             For Free, Demo classes Call: +91-8149911142
                                              Registration Link: Click Here!

Different terms used in Statistics? 

A person should have knowledge about often-used terminologies, broadly practiced in Statistics for data science. Let us understand the same -

• Population - The place or a source from where the data has to be fetched or collected. 

• Sample -  It is defined as a subset of the population. 

• Variable - Data item that can be either a number or thing that can be measured.

• Statistical Parameter -  It is defined as the quantity that leads to probability distribution like mean, median, and mode.
  
   

  What is Statistical Analysis?

   

  Statistical Analysis is the science of the exploration of the collection of large datasets to find different hidden patterns and trends. These types of analyses are used in every sort of data for example in research and multiple industries, etc so as to come to decisions that are to be modeled. There is mainly two types of Statistical Analysis- 

   

• Quantitative Analysis: The type of analysis is defined as the science of fetching and interpreting the data with graphs and numbers to search for underlying hidden trends. 

• Qualitative Analysis: The type of Statistical analysis that gives the common information by making use of text and other forms of media. 
  
  
                                                 For Free, Demo classes Call: +91-8149911142
                                                    Registration Link: Click Here!

  Measures of Central Tendency

   

  It is defined as the single value that aims to explore a set of data by recognizing the central position within the set of data. It is also called a measure of a central location that is also categorized as summary statistics. 

   

• Mean - It is calculated by taking the sum of all the values that are present in the dataset and dividing that by the number of values in the data. 

• Median -  It is the middle value in the dataset that gets in order of magnitude. It is considered over mean as it is least influenced by outliers and skewness of the data.

• Mode - It is the most occurring value in the dataset. 
   

  Conclusion 

   

  Statistics and probability are the base of data science. One should know the fundamentals and concepts so as to solve the data science problems. It gives you the information about the data, how it is distributed, information about the independent and dependent variable, etc. 

   

  In this blog, I have tried to give you the basic idea about statistics and probability. Yes, there is much more to be explored when we talk about Statistics and probability in Data Science. 

   

  We have discussed the important, central limit theorem, statistical analysis, measure of central tendency, basic terminologies in statistics, and skewness. Also, I have given you the idea of a Hypothesis done in probability and how we can accept it and reject it on the basis of a p-value.

  
  Author:-
  Anjali Mourya
  Call now!!! | NITS GLOBAL 

•