{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Math203 ch 10 notes 091

# Math203 ch 10 notes 091 - WARNING Due to the mere fact that...

This preview shows pages 1–2. Sign up to view the full content.

WARNING: Due to the mere fact that we are covering chapter 10 before chapters 5-9, we will have to do a little creative editing. You will have to pay close attention to what is being covered in the notes and compare it to that in the text. Chapter 10 INTRODUCTION Chapters 2 & 3 deal with data sets that have only one variable to consider. Often times we need to know information about two variables. Recall independent and dependent variables from chapter 1. This is what we are going to take a peek at in this chapter. We will deal with Simple Linear Regression (SLR) . In simple linear regression we are looking at the relationship between a single dependent variable and an independent variable that are both quantitative. Linear regression, in general, can have more than one independent variable and a single dependent variable. We are not going to look at that. Also, we will not cover Multiple Linear Regression (we have multiple independent variables, too). If the data is qualitative, there are other methods of dealing with the data. We are not covering those, either. Regression , in general, is defined on page 523 of your text as a statistical method used to describe the nature of the relationship between variables. For simple linear regression, we need to look for a couple things: Two (or more if it is not SLR) variables related The variables are quantitative One of the variables must be the independent variable and the other the dependent variable Each pair of data (dependent and independent variables per person/subject) must be independent of the other pairs of data. We look for the data to be positively or negatively correlated. Once we feel we have these conditions meet, we can then complete SLR to describe the relationship and predict outcomes. CORRELATION SCATTERPLOT Our first step in determining if the data is correlated is to complete a scatter plot . Scatter plots are simply the graphing of paired data on the xy-plane (which is also called the Rectangular Coordinate system, or Cartesion Plane) . My paired data will make ordered pairs (x, y). The independent variable will be my x and the dependent variable will be my y . (Independent-x, Dependent-y) Remember y depends on x . Each subject will have its own ordered pair that you will have to plot. If you have 20 subjects, you have 20 ordered pairs to plot. To plot the ordered pairs, you must first draw and label the x and y axes. Remember your y axis is always the vertical one. After you draw and label the axes, then plot the ordered pairs. You have then completed a scatter plot. Example 1– pg 549 17. Larceny and Vandalism A criminology student wishes to see if there is a relationship between the number of larceny crimes and the number of vandalism crimes on college campuses in southwestern Pennsylvania. The data are shown. Is there a relationship between the two types of crimes?

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 8

Math203 ch 10 notes 091 - WARNING Due to the mere fact that...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online