View
118
Download
1
Category
Tags:
Preview:
DESCRIPTION
Citation preview
Algebra 2 Warm up 5.4.13
Write a brief description of how to determine each statistical measure:a. Meanb. Variancec. Ranged. Mediane. Standard Deviationf. Mode
Correlation
• Correlation is relationship between 2 variables.– Example: There is a positive relationship between
the type of house you live in and the amount of money you make. The more money you make the nicer you house you probably have.
• The idea is to plot out the data and see if they all align up together on one curve.
Y
X
Y
X
Y
Y
X
X
Linear relationships Curvilinear relationships
Various Correlations
Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall
Correlation Coefficient , (r)
A number between –1 and 1, used to describe the “correlation” between 2 data points. 0 = No relationship between the data. –1 = A strong negative linear relationship 1 = A strong the positive linear relationship
The more closely aligned data is, the higher the correlation .
Scatter Plots of Data with Various Correlation Coefficients
Y
X
Y
X
Y
X
Y
X
Y
X
r = -1 r = -.6 r = 0
r = +.3r = +1
Y
Xr = 0
Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall
Y
X
Y
X
Y
Y
X
X
Strong relationships Weak relationships
Linear Correlation
Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall
Linear Correlation
Y
X
Y
X
No relationship
Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall
Example• A director of sales for Blockbuster Video wants to predict
future sales of his videos• He believes that there is a correlation between the number
of sales he will make and the number of houses that have a VCR.
• He compiles some data and makes a chart:
Example• Treating the data as ordered pairs he makes a “scatter plot” of
the data:
Example• There appears to be a “linear” relationship between the data.• They all line up pretty nicely to a straight line.• The data has a HIGH positive correlation
But what is the correlation coefficient?
• There is a nasty formula we could use to find it that looks like this:
• We won’t be using that (Thankfully)• We will be using Technology!
Regression line
• An equation that best describes the data. • Remember an equation of a line gives you
each point, so we can use this to predict!• From the technology we got:
y = 2.81 x - 15.12
X = households with VCRS ( in millions)Y = Sales
Homework
1. Think about 2 things that might be correlated.2. Create a hypothesis (or a prediction)3. Poll at a minimum 10 people.4. Record your data in a Google spreadsheet
Remember there needs to be 2 columns5. We will test your hypothesis tomorrow. Example:
• Will the number of students who are absent vary according to the temperature?
• Does the color of one’s car correlate to their income?• Will music help students study and if so what kind?
Recommended