Chapter11 - DISPLAYING THE RELATIONSHIP 1 DEFINITIONS:...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon
DISPLAYING THE RELATIONSHIP 1
Background image of page 1

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

View Full DocumentRight Arrow Icon
DEFINITIONS: Studies are often conducted to attempt to show that some explanatory variable “causes” the values of some response variable to occur. The response or dependent variable is the response of interest, the variable we want to predict, and is usually denoted by y . explanatory independent variable attempts to explain the response and is usually denoted by x . A scatterplot shows the relationship between two quantitative variables x and y . The values of the x variable are marked on the horizontal axis, and the values of the y variable are marked in the vertical axis. Each pair of observations ( x i , y i ), is represented as a point in the plot. Two variables are said to be positively associated if, as x increases, the values of y tends to increase. Two variables are said to be negatively associated if, as x increases, the values of y tends to decrease. When a scatterplot does not show a particular direction, neither positive, nor negative, we say that there is no linear association . Scatterplot of Final vs Midterm Scores Midterm 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 The 10th student (21 , 38) Final 2
Background image of page 2
Student Number X Midterm Score Y Final Score 1 39 62 2 44 69 3 32 68 4 40 86 5 45 88.5 6 46 88.5 7 33 76 8 39 66.5 9 32.5 75 10 21 38 11 30 71 12 39 88 13 44 96.5 14 28.5 71.5 15 38 96 16 43 82.5 17 42 85 18 25.5 28 19 47 95 20 36 39 21 31.5 58 22 32 49 23 42 62 24 21 59 25 41 90 Let's Do It! 1 The data below was obtained in a study of age and systolic blood pressure  of   six   randomly   selected   subjects.  Make   a   scatter   plot   to   examine   the  relationship   between   ( x )   =   age   and   ( y )   =   pressure.     Comment   on   the  relationship with respect to form, direction, strength, and any departures or  usual values. Subject Age x Pressure y A 43 128 B 48 120 3
Background image of page 3

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

View Full DocumentRight Arrow Icon
C 56 135 D 61 143 E 67 141 F 70 152 Notes of Caution 1. An observed relationship between two variables does not imply  that there is some causal link between the two variables. For example, consider the following scatter-plot of IQ score versus shoe size: IQ                                             4
Background image of page 4
    Shoe Size As a person ages their shoe size increases as well as their IQ. Although there is a  positive association, there is no causal link between the two variables shoes size and IQ. Most studies attempt to show that some explanatory variable "causes" the values of the  response to occur.  While we can never positively determine whether or not there is a  distinct   cause-and-effect   relationship,   we   can   assess   if   there   appears   to   be   such  relationship. 2. A relationship between two variables can be influenced by  confounding variables .
Background image of page 5

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

View Full DocumentRight Arrow Icon
Image of page 6
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 01/13/2012 for the course MATH 350 taught by Professor Keithemmert during the Summer '11 term at Tarleton.

Page1 / 29

Chapter11 - DISPLAYING THE RELATIONSHIP 1 DEFINITIONS:...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online