Page 40 - Intermediate Statistics for Dummies

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Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis
Getting the Big Picture: An Overview
of Intermediate Statistics
Because of the dangers and lingering effects of using the wrong techniques in
the wrong situation to analyze data to answer questions, knowing what’s hap-
pening behind the scenes of any data analysis and staying within the rules of
well-chosen techniques and appropriate practices is very important. In other
words, it’s crucial for you to take your knowledge of statistics to the next level.
Intermediate statistics is an extension of introductory statistics, so the jargon
follows suit and the techniques build on what you already know. If you’ve
been able to grasp the ideas from the first course, you’ll find no trouble with
the terminology for intermediate statistics. If you’re still unsure about some
of the terms from introductory statistics, you can consult your textbook from
your first course or see my other book, Statistics For Dummies (Wiley), for a
complete rundown. 19
In this section, you get an introduction to the terminology you use in interme-
diate statistics, and you get a broad overview of the techniques that statisti-
cians use for the purpose of analyzing data and the big picture behind them.
Population parameter
A parameter is a number that summarizes the population (the entire group
you’re interested in investigating). Examples of parameters include the mean
of a population, the median of a population, or the proportion of the popula-
tion that falls into a certain category.
Suppose you want to determine the average length of a cell-phone call among
teenagers (ages 13 to 18). You’re not interested in making any comparisons;
you just want to make a good guesstimate as to what the average time is. So
you want to estimate a population parameter (such as the mean or average).
The population is all cell-phone users between the ages of 13 and 18 years old.
The parameter is the average length of a phone call this population makes.
Sample statistic

You normally can’t study every member of an entire population (how would
you like to measure and record the length of every single cell-phone call
made by all teenagers?). So you can’t determine population parameters
exactly; you can only estimate them. But all is not lost; by taking a sample (a
subset of individuals) from the population and studying them, you can come