Design of Experiment: goal to analyze insurance claims data and climate change to show hurricane severity and increased claims are correlated.
In order to examine the risk of underestimating the frequency and severity of hurricanes for this paper, we will assume a (1) positive linear correlation between the increase in hurricane severity and claims paid; (2) a negative linear correlation in sea-surface temperature and hurricane wind speeds (recent studies estimate that a three degree centigrade increase in sea surface temperature would raise maximum hurricane wind speeds by 15 to 20 percent); and (3) a 2% per year increase over ten years in hurricane severity for the study area. Based on our review of current literature, this is a conservative estimate. We hypothesize that there is a statistically significant increase in claims paid at only 2% increase per year in hurricane severity. The null hypothesis is that although there will be an increase in claims paid, the difference will not be statistically significant. Our sample consists of two populations, in our business as usual (BAU) case, there is no impact from climate change on our study area and the number of hurricanes stays the same based on historical data, and the damages remain at the same per year AND two, in our climate change case (CCC), the intensity and frequency of hurricanes increases by 2% over the historical projections and claims increase proportionately.

Time Period Insured Losses in Tri-State Area (millions)
1950-1959 57
1960-1969 2
1970-1979 102
1980-1989 40
1990-1999 228
2000-2009 785

How would you test the hypothesis based on this data and:
Evaluate data using the appropriate test for significance
Rationale for using the test is clear
Findings are displayed clearly
Critical value is correct.
p-value testing is included