Unlock powerful data analysis skills with our CPD Accredited and Industry Standard course, “Statistical Concepts in R.” Master linear and non-linear regression, model validity, and predictive techniques through hands-on modules like Multiple Linear Regression and Logistic Regression. Enrol now to boost your analytics career with globally recognised expertise!
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In the UK, data-driven roles are growing rapidly, with over 20% increase in demand for statistical and data analysis skills in recent years. Understanding statistical concepts through R programming is now essential for professionals aiming to stay competitive. This course offers an Industry Standard pathway to grasp these crucial skills in a practical, accessible way.
You will gain hands-on experience with key statistical techniques such as simple and multiple linear regression, logistic regression, and model interpretation. The course’s practical modules guide you step-by-step through installing R and RStudio, performing analyses, and validating results. These skills directly align with real-world data challenges, ensuring your learning is relevant and immediately applicable.
Completing this CPD Accredited course enhances your employability and promotion potential in fast-growing sectors like finance, marketing, and research. With statistical expertise in R, you position yourself as a valuable asset in an evolving job market. Take this opportunity to future-proof your career with a Nationally Recognised qualification.
By completing this course, learners will be able to:Â Â
Here is what the course will cover:
This course is ideal for:Â Â
After completing the MCQ assessment, you will qualify for the CPD Certificate from HF Online as proof of your continued professional development. You can order your certificate at a cost of £10 for PDF and £29 for hardcopy certificate or both for £39.
For assessing your learning, you have to complete an automated MCQ exam. It is required for the students to score at least 60% to pass the exam. Learners can apply for the certificate after they clear the exam.
There are assignment questions provided at the end of the course. You are suggested to complete the questions to enrich your understanding of the course. You can complete this according to your preferred time. The expert tutor will provide feedback on your performance after assessing your assignment.
Completing this diploma can lead to the following UK job roles:Â Â
| Module 01: Introduction to the Course | |||
| Introduction | 00:03:00 | ||
| Module 02: Simple Linear Regression | |||
| Install R, RStudio and Basic Functionality | 00:08:00 | ||
| Basics of Linear Regression | 00:03:00 | ||
| Basics of Linear Regression continued | 00:03:00 | ||
| Module 03: Linear Regression Analysis | |||
| Linear Relationships | 00:09:00 | ||
| Line of Best Fit, SSE and MSE | 00:05:00 | ||
| Linear Regression Analysis Continued | 00:02:00 | ||
| Regression Results and Interpretation | 00:11:00 | ||
| Predicting Future Profits | 00:13:00 | ||
| Statistical Validity Tests | 00:09:00 | ||
| Statistical Validity Discussion | 00:07:00 | ||
| Module 04: Multiple Linear Regression | |||
| Multiple 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 | ||
| Module 05: Non-linear Regression | |||
| 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 | ||
| Assignment | |||
| Assignment – Statistical Concepts in R | 00:00:00 | ||
| Module 01: Introduction to the Course | |||
| Introduction | 00:03:00 | ||
| Module 02: Simple Linear Regression | |||
| Install R, RStudio and Basic Functionality | 00:08:00 | ||
| Basics of Linear Regression | 00:03:00 | ||
| Basics of Linear Regression continued | 00:03:00 | ||
| Module 03: Linear Regression Analysis | |||
| Linear Relationships | 00:09:00 | ||
| Line of Best Fit, SSE and MSE | 00:05:00 | ||
| Linear Regression Analysis Continued | 00:02:00 | ||
| Regression Results and Interpretation | 00:11:00 | ||
| Predicting Future Profits | 00:13:00 | ||
| Statistical Validity Tests | 00:09:00 | ||
| Statistical Validity Discussion | 00:07:00 | ||
| Module 04: Multiple Linear Regression | |||
| Multiple 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 | ||
| Module 05: Non-linear Regression | |||
| 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 | ||
| Assignment | |||
| Assignment – Statistical Concepts in R | 00:00:00 | ||

