Lester McRae & Sagar Patel

I. INTRODUCTIONSuperstorm Sandy was one of the most catastrophic storms to hit New Jersey. Over

72,000 homes and businesses were damaged along with hundreds of thousands of homes left without electricity for days. Schools and major Universities such Rutgers New Brunswick were closed down temporarily and many people were not able to go to work for days. Flooding, power outages, and gas shortages made transportation nearly impossible and slowed down the recovery. The total cost of damage in New Jersey added up to 36.9 billion dollars.

Our research question for this project is that does personal/household income have an influence on New Jersey citizens’ opinions of Hurricane Sandy preparation and recovery? We are using the Rutgers-Eagleton Poll to uncover issues regarding Superstorm Sandy. Specifically, preparation, recovery, and the experience (transformative event) of the New Jersey residents were the three dependent variables that were observed. In order to identify trends we used income as our independent variable to see if household income correlated with how well the residents were able to overcome the financial, mental, and health burdens that Superstorm Sandy had on New Jersey residents. If income does have an effect then we would see that higher income households would be able to tolerate the burdens caused by Sandy more efficiently than lower income households. They would personally feel that they were prepared for the storm, they are fully recovered up to date, and as a result they would feel that Superstorm Sandy was just another storm.

II. METHODS AND DATAThe dataset we are using is sponsored by the Rutgers-Eagleton Poll. It was conducted

from April 3-7, 2013. They surveyed 923 New Jersey residents who were 18 and older. The data in the survey is weighted to represent the New Jersey population. Using the 2010 U.S. census the data was weighted by gender, age, race, and Hispanic ethnicity to represent the New Jersey population. Furthermore, to validate the poll the people were randomly selected by random digit dialing. This included 736 landline respondents 187 cell phone respondents. The sampling error for adults is +/- 3.2 percentage points at a 95 confidence interval.

There were some errors regarding the poll that could have skewed the data or gave us insufficient information. For example, many of the questions had a non response category, which means that some people chose not to answer the questions. One such variable was Income. Some New Jersey residents might feel uncomfortable to share their income therefore they would not respond to this question. This can lower the response of the total number of people being surveyed and so this variable might not be a representable sample of New Jersey income. Another error in this survey could possibly have occurred due to question placement. The order the questions are asked is important to see how the people being surveyed would react to the question. For example, questions regarding Sandy are asked in a specific order. All the questions previous to the last Sandy question might generate some emotions to those being surveyed and this might result the last Sandy question (Do you think Sandy was a transformative event or just another storm) to be emotionally loaded.

III. HYPOTHESESHypothesis one states that the higher a person's income level, the more likely he or she

would have recovered from the effects of Hurricane Sandy, since a higher household income decreases the burden of the financial losses that occurred due to the storm. The damages caused by Hurricane Sandy could take a toll on families that do not have the financial support to fix the damages. Therefore, our reasoning is that the more income a family household has the less burdensome the damages caused by Sandy can be.

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Lester McRae & Sagar Patel

Hypothesis two states that the higher a person's income level, the more likely he or she was prepared for the storm, since a higher household income increases the family's ability to make necessary plans or arrangements to protect valuable assets and purchase materials such as food, medicine, and clothes to have accessible during the storm. Also, families that do not have higher income probably live in lower quality houses, which can be more prone to damages caused by Sandy.

Hypothesis three states that the higher a person's income level, the less likely he or she will think Sandy was a transformative event for New Jersey, since a higher household income increases the possibility of that household living in a wealthy community which has been able to overcome the financial losses due to the storm. Moreover, the higher income a family has the more likely they were not only better prepared for the storm but higher the chances they recovered from the storm. Therefore, they would most likely feel that Sandy was just another storm. This hypothesis is derived from the above two hypotheses.

IV. DESCRIPTION

Interpretation: Of those surveyed, 30.7% had an income less than 50K, 35.3% had an income between 50K and 100K, 14.5% had an income between 100K and 150K, and 19.5% had an income greater than 150K.

Interpretation: Eight percent of all respondents surveyed have not recovered from Hurricane Sandy, as compared to 74.9% who have completely recovered and 17.1% who have partially recovered.

Table C: PERSONALLY PREPARED AS POSSIBLE FOR STORM

Interpretation: 30.2% of all respondents surveyed personally felt they were not prepared for the storm, as compared to 69.2% who personally felt they were prepared for the storm.

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Table A: Income (4 Levels)Percent n

<50K 30.7 18150K-<100K 35.3 224100K-<150K 14.5 110>150K 19.5 131TOTAL 100.0 646

Table B: Storm RecoveryPercent n

No, not at all 8.0 47Yes, completely 74.9 345Partially 17.1 88TOTAL 100.0 480

Percent nNo 30.2 256Yes 69.8 648TOTAL 100.0 904

Lester McRae & Sagar Patel

Table D: Sandy Transformative Event

Interpretation: 88.0 percent of all respondents surveyed felt Sandy was a transformative event, as compared to 16.5% who felt that Sandy was just another storm, as compared to 1.2% who did not know what transformative meant and 2.3% do not know if Sandy was a transformative event.

V. BIVARIATE ANALYSIS

Table E: Storm Recovery*Income (4 Levels)<50K 50K-<100K 100K-<150K >150K TOTAL

No, not at all 10% 9% 5% 6% 8%Yes, completely 70% 74% 75% 76% 74%Partially 20% 17% 20% 18% 18%

TOTAL 100% 100% 100% 100% 100%n 77 122 65 86 350

Interpretation: Among those who had an income of less than 50K, 10% felt that they had not recovered from Sandy at all as compared to 9% of those who had an income between 50K and 100K, as compared to 5% of those who had an income between 100K and 150K and 6% of those who had an income greater than 150K. Among those who had an income of less than 50K, 70% felt that they had completely recovered from Sandy, as compared to 74% of those who had an income between 50K and 100K, as compared to 75% of those who had an income between 100K and 150K and 76% of those who had an income greater than 150K. Among those who had an income of less than 50K, 20% felt that they had partially recovered from Sandy, as compared to 17% of those who had an income between 50K and 100K, as compared to 20% of those who had an income between 100K and 150K and 18% of those who had an income greater than 150K.

Table F: Personally Prepared As Possible For Storm*Income (4 Levels)

<50K 50K-<100K 100K-<150K >150K TOTAL

No 35% 33% 33% 28% 33%

Yes 65% 67% 67% 72% 67%

TOTAL 100% 100% 100% 100% 100%

n 179 222 107 129 637

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Percent nTransformative 88.0 747Just another storm 16.5 139Not sure what transformative means (vol) 1.2 11Don't Know 2.3 20TOTAL 100.0 917

Lester McRae & Sagar Patel

Table G: Sandy Transformative Event*Income (4 Levels)

<50K50K-

<100K

100K-

<150K>150K TOTAL

Transformative 73% 82% 84% 76% 78%

Just another storm 21% 16% 12% 21% 18%

Not sure what transformative means (vol) 3% 1% 2% 0% 2%

Don't Know 3% 1% 2% 3% 2%

TOTAL 100% 100% 100% 100% 100%

n 180 224 110 131 645

VI. ANALYSIS DISCUSSION

Table F: H1 Statistical Test (RECOVERED * INCOME (4 Levels))Value p-value*

Pearson Chi-Square 2.200a 0.9*Cramer's V 0.056 0.9*

*significant at p < 0.05

Table H: H2 Statistical Test (PERSONALLY PREPARED AS POSSIBLE FOR STORM *

INCOME (4 Levels))Value p-value*

Pearson Chi-Square 1.874a 0.599*Cramer's V 0.054 0.599*

*significant at p < 0.05

Table J: H3 Statistical Test (SANDY TRANSFORMATIVE EVENT * INCOME (4 Levels))Value p-value*

Pearson Chi-Square 14.147a 0.117*Cramer's V 0.085 0.117*

*significant at p < 0.05

After calculating the statistics we came to the result that the hypotheses in our research did not hold at any levels. We will now go through each hypothesis and explain why the hypothesis did not hold.

For hypothesis one, which related income to storm recovery the strength, is weak because there is less than 10 percentage points between each income range. Regarding direction, the dependent variable differs from each other when compared to income. Looking at each income interval the higher the income the less individuals said they recovered from the storm, which

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Lester McRae & Sagar Patel

makes the direction negative. The higher the income more individuals said they have recovered from the storm, which makes the direction for this dependent variable positive. Finally, the higher the income fluctuated among those who said they have partially recovered from the storm; therefore, there is no clear direction for those individuals based on income. The pattern that is evident for this variable is curvilinear because there is a lot of variation of storm recovery between the income ranges. Moreover, the results for these variables are statistically insignificant because our Cramer’s V value is 0.056 and that signifies a negligible relationship. The chi-square statistic is 0.09 is greater than the alpha value of 0.05, this means we can accept the null hypothesis that income does not cause a change in storm recovery. This could be due to random error and measurement error because there was a large number of individuals who did not respond to our survey which can make our n value small so it does not efficiently represent the population of New Jersey.

For hypothesis two which related income to storm preparation the strength is weak because there is less than 10 percentage points between each income range. Regarding direction, the dependent variables differ from each other when compared to income. Looking at each income interval the higher the income the more individuals said they were prepared for the storm, which makes the direction for this dependent variable positive. The pattern that is evident for this variable is curvilinear because there is a lot of variation of storm preparation between the income ranges. Moreover, the results for these variables are statistically insignificant because our Cramer’s V value is 0.054 and that signifies a negligible relationship. The chi-square statistic is 0.599 is greater than the alpha value of 0.05; this means we can accept the null hypothesis that income does not cause a change in storm preparation. This could be due to random error and measurement error because there were a large number of individuals who did not respond to our survey which can make our n value small so it does not efficiently represent the population of New Jersey.

For hypothesis three, which related income to the individual opinion that Hurricane Sandy was a transformative event, this is weak because there is less than 10 percentage points between each income range. Regarding direction, the dependent variable differs from each other when compared to income. Looking at each income interval the higher the income the less likely individuals said they thought the storm was a transformative event, which makes the direction for this dependent variable negative. The pattern that is evident for this variable is curvilinear because there is a lot of variation of the opinion that Hurricane Sandy was a transformative event between the income ranges. Moreover, the results for these variables are statistically insignificant because our Cramer’s V value is 0.085 and that signifies a negligible relationship. The chi-square statistic is 0.117 is greater than the alpha value of 0.05, this means we can accept the null hypothesis that income does not cause a change in the opinion that Hurricane Sandy was a transformative event. This could be due to random error and measurement error because there was a large number of individuals who did not know if the storm was transformative, did not know what transformative was, and did not respond to the question which can make our n value small so it does not efficiently represent the population of New Jersey.

VII. REFERENCE: http://www.state.nj.us/governor/news/news/552012/approved/20121128e.html

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