Chapter 1 Notes What is statistics?
• We need to learn about statistics because we are constantly bombarded with numerical information. We need to be able to understand the stats that have been given to us in
an educated way, so that our decision making abilities will be maximized. Whether it is for personal or business welfare. It will also teach you how it affects you, and how your
decisions affect you based on the numerical information that is given.
• In order to make an informed decision you need to be able to
o Determine whether information is adequate or if there needs to be extra
o Summarize the information in a useful and informative matter
o Analyze the available information
o Draw conclusions
• All in all, you study statistics because data is everywhere, statistical techniques are used to make many decisions that affect our lives, and no matter what you do..every
decision you make involves data.
• DEFINITION: statistics is the organizing, presenting, and analyzing of data.
Types of statistics – descriptive and inferential statistics
• Example: the gov`t reports that the population was 31 050 700 in 2001, 31 612 895 in 2006 and an estimated 34 108 752 in 2010. This information is descriptive statistics.
• IT IS DESCRIPTIVE STATISTICS if we calculate the percentage growth from one decade to the next.
• IT ISN`T DESCRIPTIVE if we used the data to estimate the population in the year 2015 or the percentage growth from 20002015. Because these statistics are not being
used to summarize pas populations but to estimate future populations.
• Some data can be organized into frequency distribution and various charts can be used to describe data.
• The mean describes the central value of a group of numerical data.
Inferential Statistics – also called statistical inference.
• The main concern is finding something about a population based on a sample taken from that population.
• Example: only 46% of high school students can do math well and 77% can’t. These are inferences about the population (high school students) based on sample data, we
refer to them as inferential statistics.
• Inferential statistics are like “best guess” of a population value based on sample information.
• NOTE THE WORDS population and sample in the definition of inferential statistics.
• In statistics the word population consists of individuals – such as all the students enrolled at UOFT. It can also consist of objects, such as all the tires produced at Cooper
Tire and Rubber Company, the accounts receivables at the end of October for Lorrange Plastics Inc.
• To infer something about a population, we usually take a sample from the population. You take a sample in order to learn something about a population like business,
agriculture, politics, and government.
Types of Variables – Qualitative and Quantitative.
• Qualitative variable/ attribute – when the characteristic being studied is categorical or nonnumeric. Like gender, religion, phone number, car owned, eye colour.
When the data is qualitative, we are interested in how many or what percent fall in each category. For example, what percent of the population has blue eyes? Qualitative data
are often summarized in charts and bar graphs. • Quantitative variable – this is when the variable studied indicates how many or how much. Quantitative variables are either:
o discrete variables which can assume only certain values, a