"Up-North" Wisconsin

Part 1

2.
     Asian-Long Horned Beetle - Null Hypothesis: There will be no difference between the average numbers of Asian-Long Horned Beetles in Buck County compared to the average of the whole state of Pennsylvania. Alternative Hypothesis: There will be a difference between the average numbers of Asian-Long Horned Beetles in Buck County compared to the average of the whole state of Pennsylvania. Conclusion: Reject the null hypothesis. There was a difference between the average number of Asian-Long Horned Beetles in Buck County compared to the average of the whole state of Pennsylvania. There was a lower amount of these beetles found in Buck County compared to the whole state average. This part of the state does not have as much of a concern with this particular invasive species when comparing to the state average.

     Emerald Ash Borer Beetle – Null Hypothesis: There will be no difference between the average numbers of Emerald Ash Borer Beetles in Buck County compared to the average of the whole state of Pennsylvania. Alternative Hypothesis: There will be a difference between the average numbers of Emerald Ash Borer Beetle in Buck County compared to the average of the whole state of Pennsylvania. Conclusion: Reject the null hypothesis. There was a difference between the average number of Emerald Ash Borer Beetles in Buck County compared to the average of the whole state of Pennsylvania. There was a higher amount of these beetles found in Buck County compared to the whole state average. This part of the state has a concern with this invasive species when being compared to the state average.

     Golden Nematode – Null Hypothesis: There will be no difference between the average numbers of Golden Nematodes in Buck County compared to the average of the whole state of Pennsylvania. Alternative Hypothesis: There will be a difference between the average numbers of Golden Nematodes in Buck County compared to the average of the whole state of Pennsylvania. Conclusion: Reject the null hypothesis. There was a difference between the average numbers of Golden Nematodes in Buck County compared to the average for the whole state of Pennsylvania. There was a higher amount of Golden Nematodes found in Buck County compared to the whole state average. This part of the state has a concern with this invasive species when being compared to the state average.

3. 

      Null Hypothesis: There is not a difference of persons per party visiting a particular wilderness park from the 1960 study and sample taken in 1985. Alternative hypothesis: There is a difference of persons per party visiting a particular wilderness park from the 1960 study and sample taken in 1985. The corresponding probability value was 7.22 which gives an almost 100% chance that there is a difference between the studies.  

Part 2

Introduction:

     In the state of Wisconsin, the tourism board has inquired about the concept of “Up-North”. The board wants to see if there is a statistical difference between the northern and southern zones of Wisconsin. The state of Wisconsin has provided a large set of data with different variables for each county across the entire state. From the numerous variables, four will be examined to see if there is a difference between the two parts of the state. The four variables chosen include resident and non-resident deer gun licenses sold as well as resident and non-resident deer bow licenses sold.  For the purpose of this study, Highway 29 running across the state will be used as the dividing line for the northern and southern zone boundary. The map below shows the boundary what is deemed as "Up-north" for the purpose of this study (Figure 1).

Figure 1. This map shows where the boundary is representing what is the northern and southern portions of the state.

Methodology: 

     In order to start the analysis, the data needed to be manipulated to fit the objectives of the assignment. A shapefile for all the counties of the state of Wisconsin (provided in a previous lab) needed to be joined with the master data set provided by the state. Once the tables were joined, the next step was to add fields to the combined data set. Four new fields were created, one for each of the variables that were to be used for analysis.  Once the four fields were created, they needed to be filled with information that could be used for statistical testing.

     The objectives of this assignment called for Chi-Squared testing to be conducted on each of the four variables. Chi-Squared is a test that is used to compare the observed distribution to the expected distribution of a frequency. In order to complete this test absolute values have to be used. Rates, percentages or proportions are not acceptable to use in this testing.

     The variables needed to be broken up into different classes in order for Chi-Squared testing to be effective. The assignment called for the variables to be broken into four classes based on an equal interval.  After the new classes had been made, the data was then exported to a dBase table. This file type is compatible with IBM SPSS software, which is what will be used for Chi-Squared testing.

Results:

The results from this analysis were very interesting. One would expect there to be a major difference with the concept of "Up-North" and the southern part of the state. The first variable of non-resident bow deer licenses sold is shown below (Figure 2).

Figure 2 Shows the number of non-resident bow
deer licenses sold in 2005 for the state of Wisconsin.

Table 1. The result of running Chi-Squared
testing on the first variable. 

When initially looking at the map, it appears that there is an obvious difference between the two parts of the state. In the northwestern portion of the map there is an obvious cluster of higher amounts of licenses sold. This would make sense because the locations with the highest amounts of licenses sold are also closest to bordering states. The table shown above shows the results of the Chi-Squared testing (Table 1). The test is used based upon a 95% confidence rating. The result of the test show that we fail to reject the null hypothesis. There is not a statistical difference between the northern are southern parts of the states for non-resident bow deer licenses sold. Although, initial predictions based off the map seem to show there is a difference, it was statistically proven that there is no difference.

Table 2. The result of running Chi-Squared
testing on the second variable.

Figure 3 Shows the number of non-resident gun
deer licenses sold in 2005 for the state of Wisconsin.

The next variable the was used was the non-resident gun deer licenses sold. The map to the right shows the distribution of where licenses were sold (Figure 3). When comparing this to figure 2, they are very similar. Many of the areas that were high in bow licenses sold are also high in gun licenses sold. The numbers of licenses sold are higher farther inward from the borders. This map also appears to give the impression that there would be a great difference between the northern and southern parts of the state. The table shown above shows us a different perspective (Table 2). The result of the Chi-Squared test are based on a 95% confidence level. We fail to reject the null hypothesis. There is no difference between the expected results the observed results of licenses sold. 

Table 3. The result of running Chi-Squared
testing on the third variable.

Figure 3 Shows the number of resident gun
deer licenses sold in 2005 for the state of Wisconsin.

The third variable was the resident gun deer licenses sold. The map to the left shows the distribution of resident gun deer licenses sold (Figure 4). This pattern is much different than that of figure 3. The amount of licenses sold seems to correlate to areas of higher population. The counties with the highest amount of licenses sold also have a higher population. The map does not have an apparent split like the first two maps. The table above is the result of the Chi-Squared test (Table 3). The results show that we fail to reject the null hypothesis.  It shows that there is no statistical difference between the expected amounts of licenses to be sold and the observed amount of licenses sold.

Table 4. The result of running Chi-Squared
testing on the fourth variable.

Figure 4 Shows the number of resident bow
deer licenses sold in 2005 for the state of Wisconsin.

The fourth and final variable used was resident bow deer licenses sold. The map to the right shows the distribution of resident deer bow licenses sold (Figure 5). This map is very similar to that of figure 4. Many areas of higher amounts of sales also correlate to the counties with higher populations. There does not seem to be an apparent split of the state. The table above shows the results of the Chi-Squared test   (Table 4). The test was based on a 95% confidence interval. With this variable, we fail to reject the null hypothesis. There is no statistical difference between the expected amounts of licenses to be sold and the observed amount of licenses sold.

Conclusion:

The results of this lab were surprising. Initially, I had thought there would be a difference between the northern part of the state compared to the southern portion. Although the maps do appear to show a difference, there was no statistical difference between the two. It was apparent that the most popular spot for non-residents to hunt deer in the state were in the counties that bordered other states. The map does not show if that reason is because of geographical distance or if there is more opportunity for deer hunting in the border counties. 



Sources:

State of Wisconsin