Warm Up
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Transcript of Warm Up
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Warm Up
1. What is the end Behavior?2. What is the domain and range?
Friday, January 17th
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WARM UP – EOCT QUESTION 5
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SCATTERPLOTS
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Topics to Cover
Correlation vs. Causation Calculating Correlation Line of best fit Least squared regression Residual plots
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Regression
Correlation vs. Causation
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CorrelationA statistical way to measure the relationship between two sets of data.
Means that both things are observed at the same time.
CausationMeans that one thing will cause the other.
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You can have correlation without causation
There is a correlation (relationship) between the number of firemen fighting a fire and the size of the fire.
(The more firefighters at the scene means that there is a bigger fire.)
However, this doesn’t mean that bringing more firemen will cause the size of the fire to increase
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Ex 1. A recent study showed that college students were more likely to vote than their peers who were not in school.
Ex 2. Mr. Suttle noticed that there was more trash in the hallways after 2nd period than 1st period.
Ex 3. You hit your little sister and she cries
Is it Causation or Correlation?
Correlation
Correlation
Causation
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Measuring CorrelationCorrelation is measured by the
correlation coefficient, R.R is a number between -1 and 1.There are 4 traits to correlation:
1. Form
2. Direction
3. Strength
4. Outliers
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1. FORM
QuadraticLinear
No Correlation
Cubic
Exponential
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2. Direction
Negative Correlation
Positive Correlation
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Positive correlations: as x increases, y increases or as x decreases, y decreases
• The more hours the athlete practices, the better he plays.• The more efficiently a student studies, the higher his/her grades.
POSITIVE
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Negative correlations: as x increases, y decreases or as x decreases, y increases
• The more miles driven, the less gas is left in the tank.• The more often students wash their hands, the less likely they are to
get sick!
NEGATIVE
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No correlation: there appears to be no trend
NO CORRELATION
Can you give me an example?!
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3. Strength
Weak ---------------------------> Strong
R value (correlation coefficient)0 ---------------------------> 1
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Correlation Coefficient (r):
number from -1 to 1 that measure how well a line fits a set of data pairs (x , y) If r is near -1, points lie close to a line with negative
slope If r is near 1, points lie close to a line with positive
slope If r is near 0, points don’t lie close to any line
correlation of how 2 variables relate range from -1 to 1 closer to 1 or -1 the stronger the
correlation
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Put the correlation coefficients in order from weakest to strongest
Ex 1: 0.87, -0.81, 0.43, 0.07, -0.98
Ex 2: 0.32, -0.65, 0.63, -0.42, 0.04
0.07, 0.43, -0.81, 0.87, & -0.98
0.04, 0.32, -0.42, 0.63, & -0.65
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Try this: Calculate R
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Match the Correlation Coefficient to the graph
Graph Correlation Coefficients
-1-0.5
00.51
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Match the Correlation Coefficient to the graph
Graph Correlation Coefficients
-1-0.5
00.51
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Match the Correlation Coefficient to the graph
Graph Correlation Coefficients
-1-0.5
00.51
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Match the Correlation Coefficient to the graph
Graph Correlation Coefficients
-1-0.5
00.51
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Match the Correlation Coefficient to the graph
Graph Correlation Coefficients
-1-0.5
00.51
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Outliers
Data that doesn’t fit in
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A. The number of hours you work vs. The amount of money in your bank account
B. The number of hours workers receive safety training vs. The number of accidents on the job.
C. The number of students at Hillgrove vs. The number of dogs in Atlanta
Positive, Negative, or No Correlation?
Positive
Negative
No Correlation
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D. The number of heaters sold vs. The months in order from February to July
E. The number of rice dishes eaten vs. The number of cars on I-75 throughout the day
F. The number of calories burned/lost vs. The amount of hours walked
Positive, Negative, or No Correlation?
Negative
No Correlation
Positive