# Month: December 2020

## Statistics with R for Business Analysts – Random Forest

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Random Forest In the random forest approach, a large number of decision trees are created. Every observation is fed into every decision tree. The most common outcome for each observation is used as the final output. A new observation is fed into …

## Statistics with R for Business Analysts – Decision Tree

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Decision Tree Decision tree is a graph to represent choices and their results in form of a tree. The nodes in the graph represent an event or choice and the edges of the graph represent the decision rules or conditions. It is …

## Statistics with R for Business Analysts – Nonlinear Least Square

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Nonlinear Least Square When modeling real world data for regression analysis, we observe that it is rarely the case that the equation of the model is a linear equation giving a linear graph. Most of the time, the equation of the model …

## Statistics with R for Business Analysts – Time Series Analysis

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Time Series Analysis Time series is a series of data points in which each data point is associated with a timestamp. A simple example is the price of a stock in the stock market at different points of time on a given …

## Statistics with R for Business Analysts – Analysis of Covariance

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Analysis of Covariance We use Regression analysis to create models which describe the effect of variation in predictor variables on the response variable. Sometimes, if we have a categorical variable with values like Yes/No or Male/Female etc. The simple regression analysis gives …

## Statistics with R for Business Analysts – Poisson Regression

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Poisson Regression Poisson Regression involves regression models in which the response variable is in the form of counts and not fractional numbers. For example, the count of number of births or number of wins in a football match series. Also the values …

## Statistics with R for Business Analysts – Binomial Distribution

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Binomial Distribution The binomial distribution model deals with finding the probability of success of an event which has only two possible outcomes in a series of experiments. For example, tossing of a coin always gives a head or a tail. The probability …

## Statistics with R for Business Analysts – Normal Distribution

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Normal Distribution In a random collection of data from independent sources, it is generally observed that the distribution of data is normal. Which means, on plotting a graph with the value of the variable in the horizontal axis and the count of …

## Statistics with R for Business Analysts – Logistic Regression

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Logistic Regression The Logistic Regression is a regression model in which the response variable (dependent variable) has categorical values such as True/False or 0/1. It actually measures the probability of a binary response as the value of response variable based on the …

## Statistics with R for Business Analysts – Multiple Regression

(R Tutorials for Citizen Data Scientist) Statistics with R for Business Analysts – Multiple Regression Multiple regression is an extension of linear regression into relationship between more than two variables. In simple linear relation we have one predictor and one response variable, but in multiple regression we have more than one predictor variable and one …