# linear regression equations?

• Jul 16th 2009, 02:08 PM
sylverhawk
linear regression equations?
i have one problem i am stuck on, please anyone?
here is my data

Simple linear regression results:
Dependent Variable: weight
Independent Variable: length
weight = -491.00992 + 28.526619 length
Sample size: 158
R (correlation coefficient) = 0.9245
R-sq = 0.8546454
Estimate of error standard deviation: 137.34116

Parameter Estimate Std. Err. DF T -Stat P-Value
Intercept -4 91.00992 31.343002 156 -15.665696 <0.0001
Slope 28.526619 0.94191015 156 30.285923 <0.0001

Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 1.730147E7 1.730147E7 917.2371 <0.0001
Error 156 2942564.5 18862.594
Total 157 2.0244036E7

Predicted values:
X value Pred. Y s.e.(Pred. y) 95% C.I . 95% P.I.
36.5 550.2116 12.017157 (526.4743, 573.949) (277.88684, 822.53644)

i need to:
write a comment about the strength of the relationship between the 2 variables based on the correlation coefficient.
write the linear regression equation for the data
what does the linear regression predict the weight of a fish should be when the length is 36.5 cm?

thanks !
• Jul 16th 2009, 03:06 PM
pickslides
Quote:

Originally Posted by sylverhawk

i need to:
write a comment about the strength of the relationship between the 2 variables based on the correlation coefficient.

R (correlation coefficient) = 0.9245

This gives a strong positive relationship between the 2 variables

Quote:

Originally Posted by sylverhawk
write the linear regression equation for the data

using the above

weight = -491.00992 + 28.526619 length

Quote:

Originally Posted by sylverhawk
what does the linear regression predict the weight of a fish should be when the length is 36.5 cm?

weight = -491.00992 + 28.526619 length

length = 36.5 so

weight = -491.00992 + 28.526619 x 36.5