Data Visualization Graphs-ggside with ggplot
Data Visualization Graphs, Huge information is being collected through data in the business world, we must need a tool to picture of that data so we can interpret it and make decisions on time....
Category: Methods
Methods in Quantitative Statistical Analysis
Methods in Quantitative Statistical Analysis, What is hypothesis testing?. Hypothesis testing is an act in statistics whereby an analyst tests an assumption regarding a population parameter. Major four principles involved in a statistical test. Evolving a...
Completely Randomized Experimental Design
Completely Randomized Experimental Design, when do you call an experimental design a randomized design? Experimental designs in which the treatments are allocated randomly to the experimental units come under the category of randomized designs....
How to Measure Contingency-Coefficient (Association Strength)
How to Measure Contingency-Coefficient, when the hypothesis of independence of attributes in a contingency table is rejected by performing a chi-square test, ensures the association between two attributes. Such kinds of situations are interested...
Power analysis in Statistics with R
Power analysis in Statistics, there is a probability of committing an error in making a decision about a hypothesis. Hence two types of errors can occur in hypothesis, Type I error and Type II...
Principal Component Analysis in R
Principal Component Analysis in R, PCA is used in exploratory data analysis and for making decisions in predictive models. PCA is commonly used for dimensionality reduction by using each data point onto only the...
Class Imbalance-Handling Imbalanced Data in R
Handling Imbalanced Data in R, Class Imbalance classification refers to a classification predictive modeling problem where the number of observations in the training dataset for each class is not balanced. In other words, the...
Best Algorithm For Stock Prediction
Best algorithm for stock prediction, Stock Prediction-Intraday is one of the trading norms of the stock market, buy shares at the opening time of the market and then sell the same at the closing...
Exploratory Data Analysis (EDA)
Exploratory Data Analysis is one of the critical processes of performing initial investigations on data analysis. Basic idea is to discover the patterns, anomalies, test hypotheses, and check the assumptions with the help of...
Random Forest Feature Selection
Random Forest feature selection, why we need feature selection? When we have too many features or variables in the datasets and we want to develop a prediction model like a neural network will take...