OC3140 Probability and Statistics for Air-Ocean Science

Basic probability and statistics, in the air-ocean science context. Techniques of statistical data analysis. Structure of a probability model, density distribution function, expectation, and variance. Binomial, Poisson and Gaussian distributions. Conditional probability and independence. Joint distributions, covariance and central limit theorem. Transformations of random variables. Histograms and empirical distributions and associated characteristics such as moments and percentiles. Standard tests of hypotheses and confidence intervals for both one-and two-parameter situations. Regression analysis as related to least squares estimation.

Prerequisite

Calculus

Lecture Hours

3

Lab Hours

2

Statement Of Course Objectives

 

Course Learning Outcomes

By the end of this course, students will be able to:

·       define a probability distribution, fit parameters and test common METOC probability models,

·       provide a description of basic air-ocean data,

·       describe the process of sampling a time series, and describe how field experiments sample from a probability distribution,

·       estimate the mean and variance of air-ocean data,

·       test hypotheses with regard to probability distributions (including the Kolmogorov-Smirnov test), and

·       understand how statistical and ensemble prediction relate to probability models and probability sampling.