Hi i need help understanding how to do the following question

Executives at an advertisement agency hire a statistical consultant to create a model that predicts the number of ads a user will click on in a 24-hour period based on the number of hours spent browsing (measured as the number of hours that any browsing software is open on their personal computer for 24 hours) and the speed of their main network in kilobytes per second (a self-reported variable). Suppose that a model is fit to the data after log transforming the response variable, from which the following output results: Call: |m(formu|a = log(nads) ~ nbrowse + speedkbps, data = advertise) Coefcients: Estimate Std. Error t value Pr(> | t |) (Intercept) -1 .566877 0.491151 -3.190 0.00188 nbrowse 0.016206 0.007037 2.303 0.02329 speedkbps 0.030449 0.003796 8.022 1.74e-12 Residual standard error: 0.2552 on 103 degrees of freedom Multiple R-squared: 0.5628,Adjusted R-squared: 0.5544 F-statistic: 66.31 on 2 and 103 DF, p-value: