Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.
Statistics are important tools for validating theory, making predictions and engaging in policy research.
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to ...
This book helps students to gain the level of competence in statistical procedures necessary for independent investigations, field-work and other projects.
This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead.
This measure of correlation is sometimes called Pearson's correlation coefficient, to distinguish it from a nonparametric measure called Spearman's correlation coefficient, which will be introduced shortly.
The book examines the most used statistics in the field of environmental sciences.
The Pearson correlation is so widely used that you will find it in almost any data analysis software. ... It is calculated as s xxxx n i n ii 2 1 1 = −()−() − = Σ (9.1) The covariance is similar, except that it multiplies the ...
This book is aimed directly at students of geography, particularly those who lack confidence in manipulating numbers.
This is the only text you’ll need for undergraduate courses in statistical analysis, statistical methods, and quantitative geography.
... Figure 5.12 Sample SAS code for prewhitening and periodogram construction with Mauna Loa CO2 data 2 1 0 -1 Malam -2 you -3 0 0.1 0.2 0.4 0.5 Frequency Figure 5.13 Smoothed periodogram for Mauna Loa CO2 data Some analysts interpret ...