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Browsing Category

# Analytics

## What is Data Visualization: R and Tableau

"Without data you are just another person with an opinion." Be it a presentation at work, or a report submitted to your boss or just as simple as asking your parents for permission to go that trip you’ve always wanted to go to, it…

## Effect Of Multicollinearity and VIF in R

Problems Due To Multicollinearity We start the topic of Multicollinearity by giving a funny example by which we can realize what multicollinearity is and its effect. One day Ram’s father asked him “Ram, Why your bank balance is so much…

## Difference between K Means Clustering and Hierarchical Clustering

Cluster analysis or simply k means clustering is the process of partitioning a set of data objects into subsets. Each subset is a cluster such that the similarity within the cluster is greater and the similarity between the clusters is…

## Customers Segmentation Using RFM Model

Customer Lifetime Value Customers Segmentation a phenomenon to determine Customer Lifetime Value (CLV), also known as Lifetime Value (LTV), is the present value of the future cash flows from the customer during his or her entire…

## Data Mining: Market Basket Analysis in R

Market Basket Analysis in R, From Sellers to Intelligent Sellers: Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items.…

## K Means Clustering In R

K Means Clustering is used when the input data is unlabeled and we have to find hidden patterns or clusters in the data set unsupervised learning comes into the picture. In clustering what we do is given a data set we look for similarities…

## Time Series ARIMA Forecasting Using R

Time Series Forecasting Using R: A Starter Pack Some basic theoretical ideas needed before we proceed:- Time Series Data- A time series is a set of observations on the values that a variable takes at different times. Such data may be…

## Point Estimation

Point Estimation: So far we know that when the constants of a population (the parameters) are unknown, we estimate them by finding estimates based on the samples drawn from the same population. This method is called “estimation”. Now, since…

## How to Use Probability Distribution to Understand Your Data Critically

Is there any basis why probability distribution has to be talked about? What are its uses in understanding data? Can it show a sense of relevance according to one's needs? These are some of the questions that one has to ask in studying…

## Data Analytics How to Use Graphs to Present Your Data Smartly

"Data by itself is useless. It is only useful when you apply it." In Data Analytics, when we say data, these involve numbers or texts or symbols that represent some pieces of information. More often than not, we can see the numbers. Because…