A course in the preparation and analysis of quantitative data

Introduction to Quantitative Data

• Types of quantitative data
• Applications and importance in decision-making

Data Collection Techniques

• Primary vs. secondary data sources
• Sampling methods and survey design
• Collecting and managing quantitative data

Data Preparation and Cleaning

• Data entry and formatting
• Identifying and handling missing values
• Outlier detection and normalization techniques

Statistical Analysis Basics

• Descriptive statistics (mean, median, mode, standard deviation)
• Inferential statistics and hypothesis testing

Exploratory Data Analysis (EDA)

• Uncovering patterns and relationships in data
• Detecting anomalies and preparing data for analysis

Data Visualization

• Visual representation techniques (histograms, scatter plots, box plots)
• Tools for effective data visualization (Excel, Tableau, Power BI)

Advanced Quantitative Analysis Techniques

• Correlation and regression analysis
• Time series analysis and forecasting basics

Interpreting and Presenting Data Findings

• Turning data analysis into actionable insights
• Presenting findings through reports and presentations

Ensuring Data Accuracy and Reliability

• Validity and reliability in quantitative analysis
• Techniques for reducing bias and errors

Practical Applications and Case Studies

• Applying quantitative analysis in business and research
• Case studies for hands-on practice