## Math 15 Unit 1: Lesson 1

Start reading Chapter 1:

Chapter 1 really gives an overview of the whole course. It can be very overwhelming -- so try not to get too

Chapter 4 starts out by helping us learn to distinguish between different types of data. Since we will use data to help us to make decisions, it is very important to understand these different data types.

__Chapter 1 How to Make a Decision With Statistics__*If you do not have the book yet, read the Sample Chapters on the publishers website at http://esminfo.prenhall.com/math/aliaga/closerlook/popup_content_sample.htm.*Chapter 1 really gives an overview of the whole course. It can be very overwhelming -- so try not to get too

*overwhelmed*. That is, try not to get too bogged down in it. Keep in mind that the point of Chapter 1 is to give us the grand scheme of the entire course all in one fell swoop.**1.1 Introduction -- Statistics and the Scientific Method (pp 1-3)**

Make note of the**scientific method**and the circular nature of it. We will keep referring back to this process throughout the course.**1.2 Decisions, Decisions (pp 3-4)**

Statistics can help us to make informed decisions but will not generally prove anything beyond a doubt. It is important to understand how statistics are used so that we can make more informed decisions.**1.3 The Language of Statistical Decision Making (pp 4-15)**

Learning statistics is like learning a new language!

**1.3.1 Testing Theories**

Here, the word "population" is a terrific example of a word that sounds just like a word we use in English, but in Statistics, it is used in rather a different way than we are accustomed to. This will happen to us a lot. It can be very tricky. In regular English, when we hear the word "population" we generally think of a group of people (or sometimes animals). In statistics, a "population" could be a bunch of bags of potato chips, ... or an entire shipment of light bulbs ... or bolts ... not what we would 'normally' use the word "population" to describe.

In very general terms, the*null hypothesis*is the theory of*no change*from the status quo. But this itself can vary depending on the situation. We'll talk about this in class.

Note: In Example 1.1, regarding the terms "one-sided" and "two-sided" -- there is an explanation in the "What We've Learned" on p. 6. There is more on this in Section 1.4.2 (pp 23-28). Basically it boils down to an issue of, is it "less than" or "greater than" or just "not equal to"?**1.3.2 How Do We Decide Which Theory to Support?**

Important: At the bottom of p. 7, note the distinction between using the terms "accept" and "failing to reject. " This is the same reason that, at a trial, the verdict is either "guilty" or "not guilty" (but there is never a verdict of "innocent" -- innocence is presumed).

Since, in general, we cannot prove one theory is true, we must make an educated guess on which one we believe to be the true theory. Even using the same data, different people might reach different conclusions (which is why sometimes there are "hung juries"). Our choice of which theory to support is ultimately based on which seems (to us) more likely to be true.**1.3.3 What Errors Could We Make?**

The simple-looking chart in the middle of page 12 is*key*to understanding the two types of errors. (See also the "Decision Boxes" handout in the Resources folder.)

__Chapter 4 Summarizing Data Graphically__Chapter 4 starts out by helping us learn to distinguish between different types of data. Since we will use data to help us to make decisions, it is very important to understand these different data types.

**4.1 Introduction (p. 212)**

Most of Chapter 4 deals with making graphs to summarize data visually, but what we want to start out with right now is learning about the different data types.**4.2 What Are We Summarizing? (pp 212-219)**

For today, we will just look at the first subsection "Types of Variables."

**4.2.1 Types of Variables (pp 214-217)**

Look at the diagram on p. 215. The two main differences are between "qualitative" data (which are in categories) as opposed to "quantitative" data (which are numerical quantities that have numerical value). Then, within the quantitative (numerical) data, there are further sub-groupings that are important: continuous and discrete.

**4.2.2 What? How? Who? When? (pp 217-219)**

The point here is that it is important to think about the whole story behind what you see.**4.2.3 Distribution of a Variable (p 219)**

Two things to keep in mind: all the different values the variable can have, and how often those different values can occur. (Note: we use the word "*value*" even for categories. For example, if the*variable*is*car color*then one possible*value*is**blue**.)

__H__

__omework Assignment #1__Since this class is a little overwhelming at the beginning, your first homework assignment is a little non-standard and more of a setting-up nature.

**Syllabus**-- Please read through the course information and be sure to ask questions right away if you have any.**Materials**-- Get the book, get your Comp Book (so you can get started on your Reference Book right away) and be sure to have a graphing calculator. If you do not have your textbook right away, you can read Chapter 1 and Chapter 4 online (see the links from my webpage at http://online.redwoods.edu/instruct/tmatsumoto/math15/).**Reading**-- Familiarize yourself with the "Lessons" in myCR and find the Reading Assignment and read the text.**Reference Book**-- While you are reading, set up your Reference Book and start writing some information in it.**Basic Problems**--- Chapter 1 Exercises (pp 67-68) #1.1*, 1.3, 1.7*
- Section 4.2 (pp. 219-220) Exercises 4.1*, 4.3*, 4.5

**Advanced Problem**--

Chapter 1 Exercise (p. 67) #1.5**Introduction**-- Post an introduction of yourself in myCR in the Forum. Post a reply to at least two other people in the class also.

* Note: problems with "*" are minimal problems you should do; "BASIC" problems are ones everyone really should do if at all possible; "Advanced" problems should be done if you want a grade better than a "C" in the course