Cluster analysis groups data points based on similarities, allowing for segmentation and pattern recognition.
Hypothesis testing helps determine if observed results are statistically significant or due to random chance, ensuring data-driven conclusions.
A t-test is used in hypothesis testing to determine if there is a significant difference between the means of two groups.
Statistical analysis helps identify patterns, trends, and relationships in data to support decision-making and predictive modeling.
Regression analysis is used to identify relationships between independent and dependent variables, helping with prediction and trend analysis.
The mean (average) is a common measure of central tendency that represents the typical value in a dataset.
