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2.1-2.4 notes

# 2.1-2.4 notes - Chapter 2 Examining Relationships How can...

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Chapter 2: Examining Relationships How can we determine if 2 quantitative variables are related to each other? If there is a linear association, how can that information help understand and describe the data? Suppose we want to predict the assessed value of a house in a particular community. - 170

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We could select a single random sample of size n houses from the community, estimate μ , and then use this quantity to predict the house’s assessed value. A better method uses information that is available to any property appraiser – square feet of floor space and age of the house. If we measure square footage and age at the same time as assessed value, we can establish a relationship that lets us use these variables for prediction. response variable – measures an outcome of a study 171
explanatory variable – explains or influences changes in a response variable 172

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STAT3000 Section 2.1: Scatterplots Scatterplot Graphical display to determine pattern of association of two quantitative variables: Horizontal Axis: Explanatory variable , x, (input) Vertical Axis: Response variable , y, (output) Internet Usage and Gross National Product (GDP) 173
Examining a Scatterplot 174

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1. Is linear regression appropriate for the data being investigated? In any graph of data, look for the overall pattern and for striking deviations from that pattern. You can describe the overall the shape and direction of the relationship pattern by graphing a scatterplot . An important kind of deviation is an outlier, an individual value that falls outside the overall pattern of the relationship. positively correlated – an increase in one variable is generally associated with an increase in the second variable. 175
negatively correlated – one variable has a tendency to decrease as the other increases. Ex: Would you expect a positive association, a negative association or no association between the age of the car and the mileage on the odometer? Positive association Negative association No association None of the above Ex: Would you expect a positive association, a negative association or no association between the age of a full- time college student and gender? ( categorical so trick question) Positive association 176

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Negative association No association None of the above 177
Ex: The speed of a car and the distance required to come to a complete stop. Positive association Negative association No association Ex: The degree of job satisfaction and the number of absences from work. Positive association

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2.1-2.4 notes - Chapter 2 Examining Relationships How can...

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