A small statistical sample of a campaign I worked for nearly 10 years ago.

1. SUOZZI PRIMARY CAMPAIGN (2001)
Analysis for the 13TH Legislative District Nassau County, NY
Jason Zervoudakes
10 statistical analyses were made for the 13th Legislative District (9 regression
and a multiple regression with Analysis of Variance) in order to find out which
groups were more likely to vote in a Primary election. The voter histories of the
1999 General and 2000 Presidential Primary were used because of similar
turnouts. Normally, the practice is to use three elections when making these
types of analyses. However, voter history records for the 1997 election in the
county weren’t automated and therefore not included. The voter histories of the
1999 and 2000 elections were tallied and converted into percentages. The
dependent variable is the percentage of people who voted in either of the
elections. Table 1 lists all the independent variables with significant results
shaded in blue. Regression analyses confirm the group most likely to vote is
between the ages of 50 to 59. However, the campaign is safe if it targets voters
between the ages of 40 and 79. Tables 2-4 list the raw tallies.
TABLE 1- REGRESSION ANALYSES
Percentage of People Who Voted vs. Age and Gender groups
Analysis Correlation Residual Standard P-Value
Coefficient Squared Error
Age 50-59 .70 (strong) 48.3% 3.9% 0 (significant)
Age 60-69 .67 (strong) 44.5% 4.0% 0 (significant)
Age 40-49 .62 (strong) 39.6% 4.2% 0 (significant)
Age 70-79 .62 (strong) 38.2% 9.0% 0 (significant)
Age 80+ .45 (mod strong) 20.4% 4.8% 0 (significant)
Age 30-39 .32 (weak) 10.2% 5.1% .01 (significant)
Age 18-29 .20 (weak) 4.2% 5.2% .12 (not significant)
Male Percentage .89 (very strong) 78.4% 2.5% 0 (significant)
Female Percentage .94 (very strong) 87.7% 1.9% 0 (significant)
MULTIPLE REGRESSION ANALYSIS
Voter Percentage (Dependent variable) vs. Female and Male Percentage
(Independent variables)
The analysis of Variance (ANOVA) resulted in a p-value of .23 meaning the data
occurred due to chance and is insignificant. Therefore, it is irrelevant which
gender votes in a primary. The following data exemplifies this.
Average percentages

2. Male percentage was 26%. Female percentage was 24%. Overall voting
percentage was 25%
Demographics
Table 2: Overall Registrants (n= 13639)
Group Number of Percentage
Registrants
Males 5715 42%
Females 7924 58%
Age 18-29 1989 15%
Age 30-39 2214 16%
Age 40-49 3180 26%
Age 50-59 2637 19%
Age 60-69 1363 10%
Age 70-79 1570 12%
Age 80+ 686 5%
Table 3: 1999 General Election Voters (n=3877)
Group Number of Voters Percentage
Males 1719 44%
Females 2158 56%
Age 18-29 121 3%
Age 30-39 282 7%
Age 40-49 834 22%
Age 50-59 878 23%
Age 60-69 600 15%
Age 70-79 878 23%
Age 80+ 284 7%
Table 4: 2000 Primary Election Voters (n=3004)
Group Number of Voters Percentage
Males 1280 43%
Females 1724 57%
Age 18-29 140 5%
Age 30-39 245 8%
Age 40-49 691 23%
Age 50-59 701 23%
Age 60-69 426 14%
Age 70-79 614 20%
Age 80+ 187 6%