Question 1

Question 1

The yeti1 data set contains information on yeti sightings at a remote trekking site. The data record: the number of yeti sightings (count); the time (time); and the number of trekkers each season (visitors).

1. Fit a Poisson regression model that does not consider the effect of changes in the number of trekkers. For this model, what is the incident rate value for time? Hint: this is exp() of the time coefficient. Report the value to three decimal places only. (0.5 marks) (This is quiz question 1).

1. For the model that does not consider the effect of visitors what is the pseudo R² value. Report the value to three decimal places only. (0.5 marks) (This is quiz question 2).

1. For a model that does control for visitor numbers, when there is an increase in time by one unit what is the increase in the log count of yeti sightings? Report the value to three decimal places only. (0.5 marks) (This is quiz question 3).

1. For a model that does control for visitor numbers, what is the p-value for a test of over dispersion? Report the value to three decimal places only. (0.5 marks) (This is quiz question 4).

1. For a model that does control for visitor numbers, how big is the 95% Confidence Interval surrounding the time estimate? Hint: You need to calculate the confidence interval and subtract the 2.5% value from the 97.5% value for the time coefficient. This is the value on the normal scale. There is no need to apply the exp() command to the confidence interval. Report the value to three decimal places only. (0.5 marks) (This is quiz question 5).

please provide with R script

count	time	visitors
1	1	2071
0	2	2110
0	3	2148
0	4	2183
1	5	2217
2	6	2250
1	7	2285
0	8	2309
1	9	2335
2	10	2363
1	11	2396
2	12	2438
0	13	2507
2	14	2584
2	15	2666
4	16	2728
2	17	2804
3	18	2892