Advanced Training Program in Statistics and Data Analysis

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