Statistical Concepts and Application with R

Welcome to “Statistical Concepts and Application with R”! This comprehensive online course is designed to equip you with the fundamental statistical knowledge and practical skills necessary to analyze data using the powerful statistical programming language R. Whether you’re a beginner or an intermediate learner, this course will provide you with a solid foundation in statistical concepts and guide you through the process of applying them using R.

What you’ll learn:

Module 1: Introduction to Statistics and R

• Understanding the role of statistics in data analysis
• Overview of the R programming language and its statistical capabilities
• Setting up R and RStudio for data analysis

Module 2: Exploratory Data Analysis

• Data types and structures in R
• Summarizing and visualizing data using descriptive statistics and graphical techniques
• Handling missing data and outliers

Module 3: Probability and Probability Distributions

• Understanding probability concepts and terminology
• Introduction to common probability distributions (normal, binomial, etc.) and their applications in R
• Generating random numbers and sampling from distributions in R

Module 4: Statistical Inference

• Estimation and hypothesis testing
• Confidence intervals and p-values
• Performing t-tests, chi-square tests, and other common statistical tests in R

Module 5: Regression Analysis

• Simple linear regression and multiple regression
• Assumptions and diagnostics for regression models
• Interpreting regression coefficients and making predictions in R

Module 6: Data Visualization and Graphics

• Creating various types of plots (scatter plots, bar charts, box plots, etc.) in R
• Customizing plots and adding labels, titles, and legends
• Presenting data effectively through visualization

Module 7: Advanced Topics in Statistical Modeling

• Logistic regression for binary outcomes
• ANOVA (Analysis of Variance) and experimental design
• Time series analysis and forecasting in R

Module 8: Data Manipulation and Data Wrangling

• Importing and exporting data in different formats (CSV, Excel, etc.)
• Cleaning and transforming data using R packages like dplyr and tidyr
• Merging and reshaping datasets

Module 9: Reproducible Research and Reporting

• Organizing and documenting your data analysis workflow
• Generating reports and documents using R Markdown
• Creating interactive visualizations with Shiny

Module 10: Case Studies and Practical Applications

• Applying statistical concepts and techniques to real-world problems
• Analyzing datasets and drawing insights using R

By the end of this course, you will have gained a solid understanding of statistical concepts and their application using R. You will be able to analyze data, interpret statistical results, create compelling visualizations, and present your findings effectively. Whether you’re pursuing a career in data analysis, or research, or simply want to enhance your statistical skills, this course will empower you to confidently work with data using R.

Enrol now and embark on your journey to master statistical concepts and their practical implementation with R!

Why Blackboard learning:

Blackboard Learning is an online learning platform by which students from any corner of the world can learn his/her desired course. Using online learning, we assist students in realising their full potential and advancing their careers. Today, our goal is to be the world’s leading provider of online learning experiences with a global impact. By leveraging online learning, we assist students in preparing for bright futures in world-changing jobs. We provide a wide range of categories including Accounting & IT, Programming, Creative and more. Our courses are designed to stretch students intellectually through state-of-the-art online learning.