module 1: Introduction to Data Analysis Understanding Data Analysis: Purpose and Scope Overview of Excel as a Data Analysis Tool module 2:Introduction to Excel Interface and Tools Data Entry and Formatting Basic Formulas and Functions SUM, AVERAGE, COUNT, etc. Introduction to Cell Referencing (Relative, Absolute, Mixed) Module 3:Data Cleaning and Preparation Importing Data from Various Sources (CSV, Text, Databases) Data Cleaning Techniques Removing Duplicates Handling Missing Data Data Validation Working with Text Functions LEFT, RIGHT, MID, TRIM, CONCATENATE Module 4: Data Analysis Tools in Excel Sorting and Filtering Data Conditional Formatting Using PivotTables and Pivot Charts Subtotals and Summarizing Data Data Tables and Scenario Analysis Practical Exercise: Analyzing Sales Data Module 5: Advanced Functions and Formulas Logical Functions IF, AND, OR, NOT Lookup Functions VLOOKUP, HLOOKUP, INDEX, MATCH, XLOOKUP Mathematical and Statistical Functions ROUND, RANK, STDEV, MEDIAN Array Formulas Practical Exercise: Creating a Dynamic Dashboard Module 6: Data Visualization Principles of Data Visualization Creating Charts and Graphs Line, Bar, Pie, Scatter, Combo Charts Formatting and Customizing Charts Using Sparklines for Quick Insights

Course Description Running the Program Browsing the SPSS menus creating new file opening existing file importing data file variable view creating new variable Types of variables entering data descriptive statistics frequency tables graphical presentation confidence intervals for one population parameter and two population parameter testing hypothesis for one population parameter and two population parameter Analysis of Variance ANOVA Regression Analysis

الإحصاء الوصفي انواع المتغيرات الجداول التكرارية مقاييس المركز مقاييس الانتشار مقاييس الالتواء عرض اليبانات متغير واحد عرض اليبانات متغيرين فترات الثقة لمعلمة سكانية واحدة ومعلمتين سكانيتين فرضية الاختبار لمعلمة مجتمعية واحدة ومعلمتين سكانيتين تحليل التباين ANOVA تحليل الارتباط تحليل الانحدار

This course provides a comprehensive introduction to econometrics—the application of statistical methods to economic data. It equips students with the tools to model, estimate, interpret, and test economic relationships using real-world data. The course blends theory with hands-on empirical practice, emphasizing understanding the assumptions behind models, diagnosing issues like multicollinearity and heteroscedasticity, and making sound inferences. By the end of the course, students will be able to formulate econometric models, estimate parameters using regression techniques, interpret empirical results, and evaluate the reliability and limitations of statistical inferences in an economic context.