Unleashing the Power of R Packages: The Ultimate Toolkit for Data Analysis and Visualization

Population Forecast of Bangladesh: An experimentation using ARIMA modelling approach

Modeling and forecasting population in Bangladesh using ARIMA modelling approach in R Employing annual time series data on total population in Bangladesh from 1960 to 2019, we model and forecast total population over the next 20 years using the Box – Jenkins ARIMA technique. This article is presented with the following contents. Contents Introduction Method …

Hypothesis Testing – Interpreting Data with Statistical Models Introduction Building predictive models, or carrying out data science research, depends on formulating a hypothesis and drawing conclusions using statistical tests. In this guide, you will learn about how to perform these tests using the statistical programming language, ‘R’. The most widely used inferential statistic techniques …

Ensemble learning is a powerful technique in machine learning that combines the predictions of multiple models to improve the overall performance of a system. One popular ensemble method is called bagging, which stands for Bootstrap Aggregating. Bagging is a technique that generates multiple subsets of the data, and then trains a model on each …

The BJ Sales dataset from UCI (University of California, Irvine) is a collection of data that is used to analyze and forecast the number of sales of a certain product over time. Each observation represents a period of time, such as a month or a year, and the feature represents the number of sales …

The Sales dataset from UCI (University of California, Irvine) is a collection of data that is used to forecast the number of sales of a certain product over time. Each observation represents a period of time, such as a month or a year, and the feature represents the number of sales for that …

The BJ Sales dataset from UCI (University of California, Irvine) is a collection of 42 observations and 1 feature that are used to forecast the number of sales of a certain product in Beijing. Each observation represents a month, and the feature represents the number of sales for that month. The goal of this …

The BJ Sales dataset from UCI (University of California, Irvine) is a collection of 42 observations and 1 feature that are used to forecast the number of sales of a certain product in Beijing. Each observation represents a month, and the feature represents the number of sales for that month. The goal of this …

The BJ Sales dataset from UCI (University of California, Irvine) is a collection of 42 observations and 1 feature that are used to forecast the number of sales of a certain product in Beijing. Each observation represents a month, and the feature represents the number of sales for that month. The goal of …