With the data below: discuss statistical terms what is tested below, the result you found, and propose why that result might be so

Suffolk county 2003	Suffolk county 2018
PM2.5 AQI>50 DAYS: 43	PM2.5 AQI>50 DAYS: 8
Sample size: 111	Sample size: 116
# of success: 3.78	# of success: 6.90%

Hypothesize
To test whether the proportion of days that do not have "Good" air quality has changed between 2003 and 2018
p1 : 2018 proportion of successes for population 1
p2: 2003 proportion of successes for population 2
Null Hypothesis	H0: p1- p2= 0
Alternative Hypothesis	HA: p1- p2 0
Prepare
Our test statistic is the difference between our sample proportions
The sample satisfies the Random Sample requirement (assumption)
The sample satisfies the Independent Sample requirement as the samples are independent of each other.
The sample satisfies the Independent within Samples requirement as observations within each sample are independent of one another
To prove the large sample requirement, we use the pooled sample proportion
pooled sample proportion	0.23		(42 + 8)/(111 + 116)
	Successes	p1	0.00		116*.37
	Successes	p2	0.00		111*.37
	Failures	p1	89.32		116*(1-.23)
		p2	85.47		111*(1-.23)
Interpret
Our p-value (.0001) is less than our significance level (.05), so we reject the null hypothesis. We can therefore conclude that the proportions are different in the two populations.
Hypothesis test results:
Difference	Count1	Total1	Count2	Total2	Sample Diff.	Std. Err.	Z-Stat	P-value
p1- p2	8	116	42	111	-0.30941	0.055	-5.623027	<0.0001