Lectures related to Spatial Autocorrelation: Global Overview

Hypothesis Testing: A Different Perspective

Delves into a different perspective on hypothesis testing, emphasizing the p-value and significance levels.

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Introduces Geographically Weighted Regression, a spatially explicit approach to measure relationships between variables with location-specific outputs.

Confidence Intervals and Hypothesis Testing

Explores confidence intervals, hypothesis testing, and decision-making using test statistics and p-values.

Statistical Significance: Maximum Likelihood Estimation and Confidence Intervals

Explores type I and type II errors, critical values, and confidence intervals in statistical significance.

Spatial Statistics and Analysis

Covers spatial statistics, spatial variability, interpolation, uncertainty assessment, and hands-on exercises in spatial analysis and statistics.