Conditional queries: An Introduction to GIS

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Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Explores the distribution theory of least squares estimators in a Gaussian linear model, focusing on precision and confidence intervals construction.

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

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Covers the SQL language for interacting with databases through structured queries, including selecting, filtering, aggregating, and sorting data.

Explores hypothesis testing, Wilks' theorem, p-values, confidence intervals, and pivotal quantities.

Explores bivariate data analysis in applied biostatistics, covering correlation, regression, model selection, and diagnostics.

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Introduces relational query languages, focusing on algebra operators and query optimization.