Chapter 6 - Data Analysis Concepts and Observational Methods

Abstract

This chapter provides an overview of the data analysis concepts and observational methods for the study of oceans. In data analysis, observations or determinations of the value of a variable such as pressure, time, temperature, conductivity, oxygen content, and so forth are collected using oceanographic instruments at particular times and locations that are chosen through a sampling strategy. From these imperfect observations, containing both instrumental and sampling error, researchers estimate the true field and its statistical properties as a function of time and/or space. Modern instruments that measure nearly continuous vertical profiles—underway sampling systems such as expendable bathythermographs (XBTs) and acoustic Doppler current profilers (ADCPs), moored current meters, autonomous drifting and guided systems, and satellites—can generate large volumes of digital data. These large data sets can be treated statistically to identify data errors, to map fields, to generate statistical information such as means and trends, and to detect embedded time and space patterns and correlations among different observed parameters. The chapter discusses in detail about oceanographic sampling and observational error. Basic statistical concepts such as mean, variance, standard deviation, standard error, and probability density function are explained in the chapter. The chapter also discusses concepts related to variation in space and variation in time.