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Ted123
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[PLAIN]http://img705.imageshack.us/img705/1016/20481574.jpg
Is there any way of reading the intercept and the slope of the least squares regression line from the R output here?
Also assuming the simple linear regression model [itex]Y=\beta_0+\beta_1 X + \varepsilon[/itex] where [itex]\varepsilon \stackrel {\text{i.i.d.}}{\sim} N(0,\sigma^2)[/itex] and [itex]X[/itex] are the ages of the buses and [itex]Y[/itex] the maintenance costs, how can I determine whether X and Y are significantly statistically related?
The correlation coefficient is [itex]r=0.93[/itex] which implies there is strong positive linear correlation between [itex]X[/itex] and [itex]Y[/itex] but does this mean they are significantly statistically related or can I use something else to determine this?
Is there any way of reading the intercept and the slope of the least squares regression line from the R output here?
Also assuming the simple linear regression model [itex]Y=\beta_0+\beta_1 X + \varepsilon[/itex] where [itex]\varepsilon \stackrel {\text{i.i.d.}}{\sim} N(0,\sigma^2)[/itex] and [itex]X[/itex] are the ages of the buses and [itex]Y[/itex] the maintenance costs, how can I determine whether X and Y are significantly statistically related?
The correlation coefficient is [itex]r=0.93[/itex] which implies there is strong positive linear correlation between [itex]X[/itex] and [itex]Y[/itex] but does this mean they are significantly statistically related or can I use something else to determine this?
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