Data Collection and Analysis in Geomatics

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Related lectures (31)

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Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

Statistical Analysis: Hypothesis Testing and Distribution Models

Covers statistical analysis techniques, hypothesis testing, and distribution models using R software.

Statistical Analysis: Boxplot and Normal Distribution

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Genetics: Project R #2

Explores the analysis of genotypes and variants data through a Genome-Wide Association Study, focusing on the association between genetic variants and phenotypes like height.

Statistics for Data Science: Introduction to Statistical Methods

Covers the fundamental concepts of statistics and their application in data science.

Understanding Data Analysis

Covers the fundamentals of data analysis, statistical methods, and practical applications.

Data Science Essentials: Pandas, Numpy, Matplotlib

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Data Visualization: Techniques and Applications

Explores data visualization techniques, design impact, and interactive applications for effective information communication.

Data Analysis Techniques: Amplitude Shift Keying and Graphical Methods

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Structuring exploratory spatial data analysis

Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.