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Professional Diploma in Statistical Analysis Using R

Price$200.00
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9 Enrolled 730 Views
Date begin-
Date end-
TypeDiploma
CategorySTAT
CountryMalaysia
CityKuala Lumpur
PlaceVirtually

R is one of the most widely used programming languages for statistical analysis, data processing, visualization, and predictive modeling. It provides advanced and flexible tools for managing datasets, conducting statistical tests, building analytical models, and presenting results accurately and professionally.

The Professional Diploma in Statistical Analysis Using R is designed to provide participants with a structured and practical learning experience, beginning with the fundamentals of the R environment and data handling, progressing through descriptive and inferential statistical analysis, and concluding with advanced regression models and model evaluation.

The diploma places strong emphasis on practical application, enabling participants to use R effectively in academic research, institutional studies, and data-driven decision-making.

Program Objectives

  1. Develop participants’ fundamental skills in using the R environment and writing statistical scripts.
  2. Train participants to import, organize, clean, process, and visualize data.
  3. Enable participants to conduct descriptive and inferential statistical analyses using R.
  4. Build participants’ ability to construct and interpret different regression models.
  5. Train participants to evaluate statistical models and present analytical results professionally.

Diploma Modules

Level One: R Fundamentals and Data Processing
  1. Introduction to the R environment, script writing, and working with variables.
  2. Basic operations, lists, and programming loops in R.
  3. Vectors, matrices, and methods for handling them.
  4. Data importing, organization, cleaning, and processing.
  5. Fundamentals of data visualization using R.
  6. Advanced graphical representation and customization of visual outputs.
Level Two: Statistical Analysis Using R
  1. Descriptive statistics and measures of central tendency and dispersion.
  2. Correlation coefficients and significance testing using Pearson and Spearman methods.
  3. Probability distributions and applications of the normal distribution.
  4. The t-distribution and parametric and non-parametric tests using R.
  5. Analysis of Variance (ANOVA) and interpretation of results.
  6. Simple and multiple linear regression and prediction using the predict function.
Level Three: Advanced Regression Models and Model Evaluation
  1. Fundamental regression concepts and the distinction between simple and multiple regression.
  2. Building linear regression models and interpreting coefficients and results.
  3. Binary logistic regression and multinomial logistic regression.
  4. Poisson regression for count data and non-linear regression.
  5. Stepwise regression and selection of appropriate model variables.
  6. Ridge and Lasso regression and management of multicollinearity.
  7. Quadratic and polynomial regression and comparison of model performance.
  8. Model evaluation, treatment of outliers and heteroscedasticity, and graphical presentation of results.

Target Audience

  • Researchers and postgraduate students across different disciplines.
  • Faculty members and academic professionals.
  • Specialists working in statistics and data analysis.
  • Professionals in scientific, humanities, social, medical, and administrative fields.
  • Individuals seeking to learn statistical analysis using R from beginner to advanced level.
  • Staff working in research institutions, study centers, and decision-support units.

Diploma Details

  • Total Training Hours: 40 hours.
  • Number of Lectures: 20 lectures.
  • Duration of Each Lecture: 2 hours.
  • Weekly Schedule: Two lectures per week.
  • Total Program Duration: 10 weeks.
  • Training Method: Applied training combining theoretical explanation with practical exercises using R.
  • Language of Instruction: Arabic, with statistical and programming terminology presented in English where necessary.
  • Participation Fee: USD 200.

Participation Benefits

The participation fee includes:

  • A Professional Diploma Certificate in Statistical Analysis Using R.
  • Recordings of all training lectures.
  • The complete scientific and training materials.
  • Practical applications and examples used throughout the diploma.
  • Continuous follow-up during the diploma and responses to questions related to the training content.
Participation FeeUSD 200
Complete Diploma

The fee includes the certificate, recordings, training materials, practical applications, and continuous follow-up.

Organizers

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