Ch. 1: Stats Vocab

Where to begin… “But where shall I begin?” asked Alice. “Begin at the beginning,” the King said gravely, “and go on till you come to the end: then stop.” ~ Lewis Carroll, Alice’s Adventures in Wonderland

We study statistics because… …anecdotal evidence is not reliable. … we don’t wish to be lied to. … spotting trends helps us make good decisions Simply, we study statistics because we want to make sense of the world. Statistics is about how to think clearly with data.

The Three Steps to Statistics Think – Always use your head. Ask yourself where you are going and why. Show – Always let people know what you are doing. This is the mechanics aspect of Statistics. Show your calculations, graphs, and displays of your data. Tell – Always let people know what you learned. Until you’ve explained your results so that someone can understand your conclusion, the jobs not done! For point #2, most people think that this is the most important step in Statistics, but it’s not – it IS important, but not the most important. #3, this is actually the most important part of statistics.

Definitions Statistics is the science of collecting, analyzing, and drawing conclusions from data. The population of interest is the entire collection of individuals or objects about which information is desired. When you study an entire population, it is called a census. A sample is a subset of the population, selected for study in some prescribed manner.

Definitions An Individual is the objects described by a set of data. A variable is any characteristic whose value may change from one individual to another. ex: height, hair color, brand of car, GPA Data results from making observations on one or more variables. It is important to remember that data is not just a set of numbers, but a set of numbers with a context. ex: the numbers {78, 82, 83} have no meaning by themselves, but when told that they are students’ test scores, they become meaningful.

Definitions A variable is categorical (or qualitative) if the possible responses fall into categories. ex: brand of car, hair color (usually words) A variable is numerical (or quantitative) if the possible responses are numerical in nature. ex: height, AP score (usually numbers) NOTE: One way to tell the difference is to consider the question: “Would it make sense to find the average of this variable?” If you can, it’s numerical. If you can’t, it’s categorical.

Definitions Observational Study: A study that observes individuals and measures variables of interest but does not attempt to influence the responses. Experiment: A type of study that imposes some treatment on individuals in order to observe their responses.  

Definitions Population (or population of interest): The group of all people we want to know about. Sample: The smaller group we take from our population, in order to make conclusions about that larger group.  

Example 1: Critics argue that excessive video game play is a major contributor to the increase in obesity all over the world. Some doctors have begun using the Wii to help stroke victims regain movement in their arms and legs. Patients who find traditional exercise too boring or too difficult are more motivated to play the Wii games. Doctors had 12 patients play the Wii three times a week for 6 months, after which the doctors tested the movement in their arms and legs. a. What are the individuals being studied?   b. What variable is being measured?  

Example 1: Critics argue that excessive video game play is a major contributor to the increase in obesity all over the world. Some doctors have begun using the Wii to help stroke victims regain movement in their arms and legs. Patients who find traditional exercise too boring or too difficult are more motivated to play the Wii games. Doctors had 12 patients play the Wii three times a week for 6 months, after which the doctors tested the movement in their arms and legs. c. Is this variable numerical or categorical?     d. Is this an experiment of observational study?

Exit Slip: On a slip of paper, write down three new things that you learned today and two things that you’ve learned today but already knew.