Part 1
Null Hypothesis: Distance and sound level are not correlated.
Alternative Hypothesis: Distance and sound are correlated.
Fail to reject the alternative hypothesis because the significance is .000, which is less than .5 based on a 95% confidence level.
Distance vs. Sound level has a strong negative correlation and the points are situated closely around the best fit line.
Part 2
Some of the patterns I have noticed are with bachelors degrees. There is a negative correalation with percent black, percent no high school, and percent below poverty. There is also a positive correlation between bachelors degrees and percent white. The percent white is the only of these statistics to have a strong positive correlation. It is also the other way around, if there is a high percent of hispanic, black, or poverty, there is a negative correaltion with bachelors degrees.
There is also a racial divide, no race has a positive correlation with another race. This means that
Part 3
Introduction
The Texas Election Commission is interested in doing an analysis comparing the 1980 and 2008 presidential elections by county. They have provided all of the the data necessary for both years including voter turn out, percent democratic vote, and percent Hispanic population.
The purpose of this study is to determine if there is a spatial auto-correlation with the data. If there is clustering, where does it occur and how does it relate?
Methods
A shapefile of Texas counties was obtained from the American FactFinder. Hispanic county data was also obtained and added to the Texas data sheet. This data sheet was joined to the Texas counties and exported as a shapefile.
The data was then ready to be opened in Geoda to perform spatial autocorrealtion tests. A spatial autocorrelation is defined as the correlation between a variable with itself through space. First, a Moran's I test was performed on each data set.
Moran's I is a spatial auto-correlation test compares the value of the variable at any one location with the value at all other locations. Moran's I have 4 quadrants of comparisons.
Next, Local Indicators of Spatial Autocorrelation (LISA) maps were made for each variable. These maps provide a spatial component of spatial autocorrelation. It uses spatial weights to determine clustering on a visual map.
Results
For percent Hispanic, there are 2 cluster areas, low low and high high. The high high significance is shown to be close to the border of Mexico. The low low is clustered farthest away from the border. The Moran's I shows there is a strong correlation of .7787.
For the percent democratic vote in 2008, there is high high significance close to the border of Mexico. There is a low low significance on the northern border of the state. The Moran's I shows high correlation of .6957.
For the percent democratic vote in 1980, there are two high high significance clusters, one close to the southern border of Texas and Mexico and one to the east north border. There is low low significance cluster close to the northwestern border. The Moran's I shows a strong correlation of .5752.
The voter turnout in 1980 shows a low low significance cluster close to the southern border of Texas and Mexico. There is a high high significance in the northern side of the state, clustering around both Dallas and Austin TX. The Moran's I shows a significance of .3634.
The voter turnout in 2008 shows a low low significance cluster close to the southern border of Texas and Mexico. There a high high significance near the northern border and also clustered around where Austin, TX is. The Moran's I shows a significance of .4681.
Figure 1
From the comparison of 1980 and 2008 elections, some interesting patterns have revealed them self through both LISA and Moran's I spatial auto-correlation tests. There is a high correlation of Hispanic populations near the southern border of Texas and Mexico. On this same border, there is a high correlation of low numbers of voter turnouts, and high number of democratic votes. This means that areas that have high Hispanic clustering also have low voter turnouts, and high democratic votes in relation to them self.
There also is shown to be low hispanic spatial auto-corelations in the northern part of the state, excluding the area of Dallas TX. The area of Dallas TX Texas shows high voter turnout, but no significance of democratic vote. The northwestern part of the state shows no significance of Hispanic clustering, but high significance of voter turnout, and low democratic vote.
If the TEC is trying to increase voting in the state, the should focus on the southern border of Texas and Mexico. There is a trend of low voter turnout there, so it would be beneficial if someone was able to get these areas to vote, and the turnout is mostly democratic. This area also has clustering of Hispanic populations so that should be put into consideration also.
