Page 47 - Clackamas County Watertourism Strategic Plan. Final.v3

STRATEGIC PLAN FOR WATER-BASED TOURISM IN CLACKAMAS COUNTY, OREGON THE PEOPLE
4-5

Table 4-4: Unweighted vs Weighted Responses for Favorite Water Recreation
Unweighted Responses Weighted Responses

Angler Motor Paddler All Angler Motor Paddler All
Fly Fish 313 21 50 37% 285,329 10,254 2,537 43%
Other Fish 64 43 32 13% 58,342 20,996 1,624 12%
Flat Water Kayak 82 15 59 15% 74,751 7,324 2,994 12%
Bass Fish 48 18 8 7% 43,757 8,789 406 8%
Sea Fish 55 28 15 9% 50,138 13,672 761 9%
WhiteWater Raft 24 8 24 5% 21,878 3,906 1,218 4%
Motor Boat 40 43 19 10% 36,464 20,996 964 8%
Swim Wade 22 14 3 4% 20,055 6,836 152 4%
Sum Valid 648 190 210 100% 590,713 92,775 10,657 100%

Only this question was weighted. All other results presented in this report are in their unweighted form because it is statistically inaccurate to conduct bivariate and multivariate
analysis on weighted data. The reader must keep in mind that these results under or over represent certain populations and an estimation on the degree to which this occurs is
provided here. Nonetheless, the number of completed surveys is over 4 times the number needed to complete a statistically representative sample. Therefore, for the purposes
of creating strategies to attract more water-based tourism in Clackamas County, these data provide reliable, robust results and valuable information.
Analytical Methods
Survey data were re-coded as needed and were entered into an SPSS statistical software package. Three main types of analysis were done:
• Bivariate. How does one variable (e.g., the response to one question or membership in a demographic group) influence the response to another variable (question). For
example, how do anglers, motorboaters and paddlers differ in their favorite water bodies?
• Multivariate. How do two variables (1-anglers, motorboaters and paddlers) and (2-what county do you live in) influence a response to a question (e.g.: what is your favorite
water body)?
• Regression. How do a set of variables influence another variable (e.g.: how does gender, income, age, location and favorite sports influence the favorite water body)?

For each analysis, a test of statistical significance was done (Chi Square and ANOVA for bivariate and multivariate, F- and T-tests for regression) on the null hypothesis. In this
study, the null hypothesis is that one variable has no influence on another. A relationship is said to be statistically significant (SS) if the survey was repeated, we would very likely
find the same relationships. Significance is measured by the p-value, which is the probability that the null hypothesis would be true, given the distribution of data. Standard