Excel

Covers the basics of the Excel interface, how to navigate it, and how to make the most of key features including charts, formulas, functions, macros, and more. Walks you through creating worksheets, working with formulas and functions, formatting data, using financial functions, displaying data in PivotTables, and much more.

With examples from the world of science, this reference teaches scientists how to create graphs, analyze statistics and regressions, and plot and organize scientific data. Scientists can learn the tips and techniques of Excel--and tailor them specifically to their experiments, designs, and research. They will learn when to use NORMDIST vs NORMSDist and CONFIDENCE vs Z, how to keep data-validation lists on a hidden worksheet, use pivot tables to chart frequency distribution, generate random samples with various characteristics, and much more.

Topics include: Working with external databases PivotTables and PivotCharts Using Excel for statistical and financial functions Solver, Small Business Finance Manager, and more The book also includes a guide to chart types and formatting, and advice on effective visual data presentation.

How to leverage relational databases, slice data into various views to gain different visibility perspectives, create eye-catching visualizations and dashboards, automate SQL Server data retrieval and integration, and publish dashboards and reports to the web.

Covers how to build a chart, work with pivot tables, group and bucket your data, represent trends, create What-If analyses, and increase the value of your reports.

Statistical approaches covered include: data exploration; tests for difference - t-test and U-test; correlation - Spearman's rank test and Pearson product-moment; association including Chi-squared tests and goodness of fit; multivariate testing using analysis of variance (ANOVA) and Kruskal-Wallis test; and multiple regression. Key skills taught in this book include: how to plan ecological projects; how to record and assemble your data; how to use R and Excel for data analysis and graphs; how to carry out a wide range of statistical analyses including analysis of variance and regression; how to create professional looking graphs; and how to present your results. ALSO AVAILABLE IN PAPER.