Data Analysis Techniques for MBA Business Capstone Projects

Data analysis is a critical part of your MBA Capstone project. Understanding how to process and interpret the data you collect will enable you to draw meaningful insights and support your recommendations.

2.1 Descriptive Analysis

Descriptive analysis helps summarize and describe the characteristics of the data. It’s useful for presenting an overview of your data in a clear and digestible format.

• Measures of Central Tendency: Includes the mean (average), median, and mode to describe the central point of the data.
• Measures of Dispersion: Includes the range, variance, and standard deviation, which help understand the spread of the data.

2.2 Inferential Analysis

Inferential statistics allow you to make predictions or inferences about a population based on a sample of data. This is often used to test hypotheses and understand relationships between variables.

• Hypothesis Testing: Using statistical tests like t-tests or ANOVA to determine if differences between groups are statistically significant.
• Correlation and Regression Analysis: Analyze the relationship between variables (e.g., how marketing spending correlates with sales growth).

2.3 Predictive Analysis

Predictive analysis uses historical data to forecast future trends and outcomes. Techniques like regression models, time series analysis, and machine learning algorithms can be used to predict sales, customer behavior, or market trends.