# 1: One-Variable Statistics - Basics

• 1.1: Terminology - Individuals/Population/Variables/Samples
Oddly enough, it is often a lack of clarity about who [or what] you are looking at which makes a lie out of statistics. Here are the terms, then, to keep straight: The units which are the objects of a statistical study are called the individuals in that study, while the collection of all such individuals is called the population of the study. Note that while the term “individuals” sounds like it is talking about people, the individuals in a study could be things, even abstract things like even
• 1.2: Visual Representation of Data I - Categorical Variables
Suppose we have a population and variable in which we are interested. We get a sample, which could be large or small, and look at the values of the our variable for the individuals in that sample. We shall informally refer to this collection of values as a dataset. In this section, we suppose also that the variable we are looking at is categorical. Then we can summarize the dataset by telling which categorical values did we see for the individuals in the sample, and how often we saw those value
• 1.3: Visual Representation of Data II - Quantitative Variables
Now suppose we have a population and quantitative variable in which we are interested. We get a sample, which could be large or small, and look at the values of the our variable for the individuals in that sample. There are two ways we tend to make pictures of datasets like this: stem-and-leaf plots and histograms.
• 1.4: Numerical Descriptions of Data I: Measures of the Center
Oddly enough, there are several measures of central tendency, as ways to define the middle of a dataset are called. There is different work to be done to calculate each of them, and they have different uses, strengths, and weaknesses.
• 1.5: Numerical Descriptions of Data, II: Measures of Spread
• 1.6: Exercises