Interpret the slope and intercept of the regression model-


Oakland passengers. The scatterplot below shows the number of passengers departing from Oakland (CA) airport month by month since the start of 1997. Time is shown as years since 1990, with fractional years used to represent each month. (Thus, June of 1997 is 7.5 - halfway through the 7th year after 1990.) www.oaklandairport.com.

2058_Graph.jpg

Here's a regression and the residuals plotted against Years since 1990:

697_Graph 1.jpg

a) Interpret the slope and intercept of the regression model.

b) What does the value of say about how successful the model is?

c) Interpret in this context.

d) Would you use this model to predict the numbers of passengers in 2010 (YearsSince1990 = 20)? Explain.

e) There's a point near the middle of this time span with a large negative residual. Can you explain this outlier?

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Basic Statistics: Interpret the slope and intercept of the regression model-
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