The British Academy for Training and Development offers this training program in Statistics and Data Analysis, designed to equip participants with modern statistical methods for analyzing data and making decisions based on accurate numerical results. This program reflects the growing need across institutions for quantitative tools that support understanding trends, identifying issues, and measuring the effectiveness of plans and programs in a scientific manner.

The program focuses on building a strong knowledge base in statistics, combining theoretical understanding with practical data-analysis skills. It enables participants to work with raw data and extract meaningful indicators that support decision-making across various work environments, including government institutions, private companies, research centers, and nonprofit organizations.

The program also covers essential statistical concepts, data collection and organization methods, graphical representation techniques, probability applications, hypothesis testing, analysis of variance, and regression. Additionally, participants receive hands-on training using data-analysis software such as Excel and SPSS to apply theoretical knowledge in real-world scenarios.

Who Should Attend?

• Employees in planning and strategic analysis departments

• Statisticians and analysts working in the public and private sectors

• Academics and researchers in social and economic sciences

• Database and information systems administrators in organizations

Knowledge and Benefits:

After completing the program, participants will be able to master the following:

• Understand statistical fundamentals related to data collection, interpretation, and analysis

• Use appropriate statistical tools to summarize and visually present data

• Apply concepts of probability distributions and statistical inference in analysis

• Analyze relationships between variables using advanced statistical methods

• Apply data-analysis software such as Excel and SPSS in practical analytical tasks

• General Concepts of Statistics and Data

  • Differences between qualitative and quantitative data

  • Data sources and their importance in analysis

  • Types of statistical scales and their uses

• Data Collection and Organization Methods

  • Surveys, observations, and interviews

  • Coding and grouping techniques

  • Creating frequency distribution tables

• Measures of Central Tendency and Dispersion

  • Mean, median, and mode

  • Standard deviation, variance, and range

  • Interpreting the significance of these measures in analysis

• Graphical Representation of Data

  • Graphs: bar charts, pie charts, box plots

  • Using graphs to illustrate patterns and trends

  • Software tools for visualizing data

• Basics of Probability in Statistical Analysis

  • Mathematical definition of probability

  • Probability rules: addition and intersection principles

  • Applications of probability in decision-making

• Common Probability Distributions

  • Normal distribution and its properties

  • Binomial and Poisson distributions

  • Using statistical tables

• Statistical Hypothesis Testing

  • Formulating null and alternative hypotheses

  • Determining significance level and p-value

  • Steps of hypothesis testing and decision-making

• Analysis of Variance (ANOVA) and Regression

  • One-way ANOVA

  • Introduction to simple linear regression

  • Reading results and interpreting coefficients

• Data Analysis Using Excel or SPSS

  • Entering and organizing data in the software

  • Performing descriptive and inferential analyses

  • Extracting results and generating explanatory reports

• Interpreting Statistical Results and Decision-Making

  • Translating numbers into practical conclusions

  • Avoiding common analysis errors

  • The role of statistical analysis in institutional performance improvement