Statistics Training – KHDA Approved Program
Build a strong foundation in statistics from descriptive analysis and probability to hypothesis testing and statistical modeling. With our KHDA-approved Statistics Training program, you’ll learn to analyze data, interpret results, and support data-driven decision-making across industries such as healthcare, finance, research, and business analytics, aligned with global standards and Dubai’s professional landscape.
Course Duration: 15 - 20 weeks
Delivery Mode:Classroom / Online / Blended
Statistics Training – Program Overview
The Training Course in Statistics is a 15–20 week (70-hour) practical program designed to develop strong statistical thinking and data interpretation skills for modern data-driven roles. Learners gain hands-on experience in descriptive and inferential statistics, probability, correlation, regression, and hypothesis testing using tools such as Excel and SPSS. The program blends statistical foundations with applied analysis, enabling participants to confidently support data-driven decisions across business, healthcare, finance, and technology sectors.
Statistics Training in Dubai - Who is it for?
- Students, graduates, and entry-level professionals building strong foundations for data analysis and analytics careers
- IT professionals and aspiring data analysts developing statistical skills for data analysis, reporting, and analytics roles
- Business analysts, market research analysts, and marketing professionals using statistics for decision-making and performance analysis
- R&D managers and quality assurance professionals applying statistics for research, validation, and process improvement
Skills You’ll Develop with Our Statistics Course in Dubai
Gain core analytical and problem-solving skills required for statistics-driven roles.
Descriptive Statistics
Understand and summarize data using measures of central tendency and dispersion
Learn probability concepts and common distributions used in real-world analysis.
Inferential Statistics
Apply hypothesis testing and confidence intervals to draw conclusions from data.
Statistical Modeling
Build and interpret regression models to understand relationships and trends.
Software, Tools & Programming
Statistics Training Course Curriculum Basic Level Curriculum (70 Hours)
Module 1: Introduction to Statistics
- Meaning and scope of statistics
- Importance of statistics in decision making
- Types of statistics (Descriptive and Inferential)
- Applications of statistics in business and healthcare
- Limitations of statistics
Module 2: Organization of Data
- Collection of data
- Types of data (Primary and Secondary)
- Methods of data organization
- Frequency distribution
- Raw data vs grouped data
Module 3: Classification and Tabulation of Data
- Principles of data classification
- Types of classification
- Tabulation techniques
- Parts of a statistical table
- Objectives of tabulation
Module 4: Graphical Representation
- Importance of graphical presentation
- Bar diagrams and pie charts
- Histogram and frequency polygon
- Ogive curves
- Interpretation of graphs
Module 5: Measure of Central Tendency
- Arithmetic mean
- Median
- Mode
- Merits and demerits of averages
- Applications of central tendency
Module 6: Measure of Dispersion
- Range
- Quartile deviation
- Mean deviation
- Standard deviation
- Coefficient of variation
Module 7: Measure of Skewness
- Concept of skewness
- Types of skewness
- Karl Pearson’s coefficient of skewness
- Bowley’s coefficient of skewness
- Interpretation of skewness
Module 8: Correlation and Regression
- Meaning of correlation
- Types of correlation
- Methods of measuring correlation
- Regression analysis
- Regression equations
Module 9: Interpolation and Extrapolation
- Meaning of interpolation
- Methods of interpolation
- Meaning of extrapolation
- Uses of extrapolation
- Limitations of forecasting
Module 10: Probability
- Concept of probability
- Classical and empirical probability
- Addition and multiplication theorems
- Conditional probability
- Applications of probability
Curriculum for Advanced Level (80 hours)
Module 1: Vital of Statistics
- Meaning and scope of statistics
- Functions of statistics
- Importance of statistics in decision making
- Limitations of statistics
- Statistical investigation process
Module 2: Index Numbers
- Meaning of index numbers
- Types of index numbers
- Methods of constructing index numbers
- Consumer price index
- Uses and limitations of index numbers
Module 3: Time Series
- Meaning of time series
- Components of time series
- Trend analysis
- Seasonal variations
- Forecasting techniques
Module 4: Theoretical Distribution
- Probability distributions
- Binomial distribution
- Poisson distribution
- Normal distribution
- Applications of distributions
Module 5: Statistical Inference
- Sampling techniques
- Estimation
- Confidence intervals
- Hypothesis testing
- Type I and Type II errors
Module 6: Operation Research
- Linear programming
- Transportation problems
- Assignment problems
- Queuing theory
- Decision-making models
