Statistical Concepts and Application with R
Statistical Concepts and Application with R
- Interactive video lectures by industry experts
- Developed by qualified first aid professionals
- Instant e-certificate and hard copy dispatch by next working day
- Fully online, interactive course with audio voiceover
- Self paced learning and laptop, tablet, smartphone friendly
- 24/7 Learning Assistance
- Discounts on bulk purchases
Main Course Features:
- Comprehensive coverage of fundamental statistical concepts and techniques
- Hands-on tutorials for applying statistical methods using R programming
- Exploration of data visualization techniques for analyzing and interpreting data
- Practical exercises and projects to reinforce learning and application
- Real-world case studies demonstrating the application of statistical analysis in different domains
- Access to datasets and resources for practicing statistical analysis with R
- Supportive online community for collaboration and assistance throughout the course
- Regular assessments and quizzes to track progress and reinforce learning
Learning Outcomes
- Understand key statistical concepts and methods for data analysis
- Gain proficiency in using R for statistical computing and analysis
- Perform exploratory data analysis and visualization using R
- Apply statistical techniques to solve real-world problems and make data-driven decisions
- Develop practical skills through hands-on exercises and projects
- Build a portfolio of statistical analysis projects showcasing proficiency in R
- Communicate insights effectively through data visualization and interpretation
- Stay updated with the latest advancements and best practices in statistical analysis with R.
Who Should Take This Course
- Data analysts and scientists seeking to enhance their statistical analysis skills using R
- Researchers and professionals in fields such as finance, healthcare, and social sciences
- Students pursuing degrees in statistics, data science, or related fields
- Anyone interested in learning how to use R for statistical analysis and data visualization
Certification
Once you’ve successfully completed your course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post. All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.
Assessment
At the end of the course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.
Course Curriculum
Introduction 
00:03:00
Install R, RStudio and Basic Functionality 00:08:00 Basics of Linear Regression 00:03:00 Basics of Linear Regression Ctnd 00:03:00 Linear Regression Analysis 00:09:00 Linear Relationships 00:09:00 Line of Best Fit, SSE and MSE 00:05:00 Linear Regression Analysis Ctnd 00:02:00 Regression Results and Interpretation 00:10:00 Predicting Future Profits 00:13:00 Statistical Validity Tests 00:09:00 Statistical Validity Discussion 00:07:00 Single Linear Regression 00:06:00
Single Linear Regression 00:06:00 Importing the data 00:04:00 Correlation Matrix and MLR 00:08:00 MLR Results and ANOVA 00:07:00 The Best Model? 00:05:00 Interaction Terms and Validity Testing 00:18:00 ANOVA and Predictions 00:18:00
Non-linear Regression (and Recap) 00:07:00 Logistic Regression Overview 00:22:00 Logistic Regression: Odds, Logs and Poisson 00:13:00 Logistic Regression: Fitting the Models in R 00:24:00
Differential Calculus – Finding the Maximum and the Minimum 00:15:00 Differential Calculus: One Unknown Input 00:08:00 Analysis in R: One Unknown Input Differential Calculus 00:29:00 Differential Calculus – Two Unknown Inputs 00:07:00 Analysis in R: Two Unknown Inputs Differential Calculus 00:44:00
Resource – Statistical Concepts and Application with R 00:00:00
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