BUS 210 Study Guide - Midterm Guide: Time Series, Contingency Table, Categorical Variable
Document Summary
Goal of data analysis: to present data in a way that makes sense to people and clearly stands out (tools include graphs, numerical summary measures, tables of summary measures) There are many ways to summarize numerical values, both with numerical summary measures and with charts: measures of central tendency, average, median, mode functions, minimum, maximum, percentiles, and quartiles, measures of variability. If all observations are close to the mean, variance will be relatively small. There are many graphical ways to indicate the distribution of a numerical variable: for cross-sectional variables, histograms, based on binning the variable 0 that is, dividing it up into discrete categories. Even if the values are not unusual by themselves, there still might be unusual combinations of values. When dealing with outliers, it is best to run analyses two ways: with the outliers and without them. Most real data sets have gaps in the data.
