I had done a regression in Excel, and the p value was 2.14E-05 while the R- value was 0.32. I was told the R value was too low compared to the significance of the p value, and was told to control for the dispersion of the data by running it through R with GLM with quasipoisson error.

This gave me

glm(formula = encno ~ temp, family = quasipoisson(link = log), data = encnotemp)

Deviance Residuals: Min 1Q Median 3Q Max

-6.008 -2.431 -1.021 1.353 9.441

Coefficients: Estimate Std. Error t value Pr(>|t|)

(Intercept) 2.005807 0.174628 11.486 < 2e-16 ***

temp 0.029065 0.006528 4.453 1.53e-05 ***

Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for quasipoisson family taken to be 10.19898)

Null deviance: 1807.4 on 171 degrees of freedom

Residual deviance: 1620.1 on 170 degrees of freedom AIC: NA

Number of Fisher Scoring iterations: 5

How do I analyse this output?

The problem is that the scatterplot data is too dispersed, and I would like to make a scatterplot from the quasipoisson GLM output that shows less dispersed (more fitted) data points. Will this be possible?

Thank you!