Linear Correlation Coefficient I have used a statistical package to get this gra

Question

Linear Correlation Coefficient

I have used a statistical package to get this graph and estimates now I need help with this:

- Interpret the meaning of the slope of the LSR line.

- Based on the equation of LSR line, what is the “best predicted” value for the NYC Annual Average Temperature for 2013? How accurate is the prediction?

- Can we use this LSR line equation to predict the Annual Average Temperatures for the future? Explain.

Milan Simple linear regression results:
Dependent Variable: MilTemp
Independent Variable: Year
MilTemp = 9.9762766 + 0.024102897 Year
Sample size: 145
R (correlation coefficient) = 0.59358335
R-sq = 0.35234119
Estimate of error standard deviation: 1.3773481

Milan Parameter estimates: Parameter EstimateStd. Err.AlternativeDFT-Stat P-value Intercept Slope 0.024102897 0.0027327044 9.9762766 5.3054124 0 143 1.880396 0.0621 0 143 8.820 1625

Explanation / Answer

The slope is interpreted in algebra as rise over run. If, for example, the slope is 0.024102897, you can write this as 0.024102897/1 and say that as you move along the line, as the value of the X variable increases by 1, the value of the Y variable increases by 0.024102897.

Here LSR line is MilTemp = 9.9762766 + 0.024102897 Year

Now for x=2013, MilTemp = 9.9762766 + 0.024102897 *2013=58.495408261

Yes we can use LSR line equation to predict the Annual Average Temperatures for the future

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