# Using Excel in data analysis

This resource has been authored by David Whigham, Senior Lecturer in Economics at Glasgow Caledonian University.

The workbooks contain instructions and practical examples to help you make the most of using Excel in data analysis.

Excel 1: Basic Excel Techniques

Topics covered: Excel preliminaries, including: definitions and data types; customizing, sheet operations (inserting sheets, naming sheets, linking sheets, selecting areas of sheets); saving and printing; naming cells; copying (fully relative copying and dollar fixing); IF statements; vlookup function; and sumproduct function.

Excel 2: Descriptive Statistics

Topics covered: Weighted Average; If Statement; central tendency; dispersion (variance, standard deviation, quartiles and interquartile range); frequency distributions; descriptive statistics; ranking data; correlation (Pearson's correlation coefficient); and rank correlation (Spearman's rank correlation coefficient).

Excel 3: Contingency Tables (Cross Tabulation)

Topics covered: Two way pivot (contingency) tables and three way pivot (contingency) tables, including: Absolute count, percentage count, and averages; refreshing data in contingency tables; and categorizing data with contingency tables.

Excel 4: Charting and Regression

Topics covered: Charts, including: line, column, bar, and scatter charts; trend lines (both linear and quadratic), linear regression, time series, multiple regression.

Excel 5: Inference (Statistical Significance)

Topics covered: Inference and statistical significance, including: inferences about the population mean; the difference between two population means; the population regression coefficients; the association between categorical variables, The Chi Squared Statistic; and the population regression coefficients.