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Statistical Concepts in R

£279 £39
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Overview:

Welcome to "Statistical Concepts in R!" This course provides an in-depth exploration of statistical concepts and their implementation using the R programming language. Statistical analysis plays a vital role in various fields, including finance, healthcare, and social sciences. In this course, you'll learn essential statistical concepts such as hypothesis testing, regression analysis, and probability distributions, and how to apply them using R for data analysis and decision-making.
  • Interactive video lectures by industry experts
  • Instant e-certificate and hard copy dispatch by next working day
  • Fully online, interactive course with Professional voice-over
  • Developed by qualified first aid professionals
  • Self-paced learning and laptop, tablet, smartphone friendly
  • 24/7 Learning Assistance
  • Discounts on bulk purchases

Main Course Features:

  • Comprehensive coverage of essential statistical concepts and techniques
  • Hands-on tutorials for implementing statistical methods using R
  • Practical exercises and real-world examples for reinforcement and application
  • Exploration of data visualization techniques to interpret statistical results effectively
  • 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
  • Guidance on best practices and common pitfalls in statistical analysis with R

Who Should Take This Course:

  • Data analysts, scientists, and researchers looking to enhance their statistical analysis skills using R
  • Students pursuing degrees in statistics, data science, or related fields
  • Professionals in finance, healthcare, marketing, and other industries requiring statistical analysis
  • Anyone interested in learning how to use R for statistical analysis and data visualization

Learning Outcomes:

  • Understand fundamental statistical concepts and their application in data analysis
  • Gain proficiency in using R for statistical computing and analysis
  • Perform hypothesis testing, regression analysis, and other advanced statistical techniques
  • Interpret and visualize statistical results effectively using R
  • Apply statistical methods to real-world datasets and scenarios
  • Develop critical thinking and problem-solving skills through hands-on exercises
  • Build a portfolio of statistical analysis projects showcasing proficiency in R
  • Communicate insights and findings clearly through data visualization and interpretation.

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 (shipping cost £3.99). 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.

We guarantee that all our online courses will meet or exceed your expectations. If you are not fully satisfied with a course - for any reason at all - simply request a full refund. We guarantee no hassles. That's our promise to you.

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Course Curriculum

Module 01: Introduction to the Course
Introduction
Module 02: Simple Linear Regression
Install R, RStudio and Basic Functionality
Basics of Linear Regression
Basics of Linear Regression continued
Module 03: Linear Regression Analysis
Linear Relationships
Line of Best Fit, SSE and MSE
Linear Regression Analysis Continued
Regression Results and Interpretation
Predicting Future Profits
Statistical Validity Tests
Statistical Validity Discussion
Module 04: Multiple Linear Regression
Multiple Linear Regression
Importing the data
Correlation Matrix and MLR
MLR Results and ANOVA
The Best Model?
Interaction Terms and Validity Testing
ANOVA and Predictions
Module 05: Non-linear Regression
Non-linear Regression (and Recap)
Logistic Regression Overview
Logistic Regression: Odds, Logs and Poisson
Logistic Regression: Fitting the Models in R