Data Analysis & Quantitative Testing

Research question 1: Does age affect millennial score?
Independent variable: age
Dependent variable: Millennial score.
Hypothesis: Younger the age the higher the Millennial score
Null Hypothesis: Age will have no affect on the millennial score

The results indicate that age does have a significant impact on the millennial score. I was able to find this out by sorting the data into two age ranges. The first being under 30 years of age, and the second were individuals over 30. See below for details.

t-Test: Two-Sample Assuming Equal Variances
	Under 30	Over 30
Mean	78.1875	62.36364
Variance	490.2958333	499.2545
Observations	16	11
Pooled Variance	493.8793182
Hypothesized Mean Difference	0
df	25
t Stat	1.817927518
P(T<=t) one-tail	0.040539511	0.05	Sig.Diff.
t Critical one-tail	1.708140745
P(T<=t) two-tail	0.081079022
t Critical two-tail	2.059538536

Research Question 2: Is there a correlation between teaching status and the Millennial score
Independent variable: teaching status     
Dependent variable: millennial score
Hypothesis: A correlation will exist between teaching status and the millennial score
Null Hypothesis: No correlation will exist

The results indicate that teaching status does have a significant impact on the millennial score. See below for details.

t-Test: Two-Sample Assuming Equal Variances
	Teaching	Not Teaching
Mean	68.15789474	88.125
Variance	489.251462	92.41071
Observations	19	8
Pooled Variance	378.1360526
Hypothesized Mean Difference	0
df	25
t Stat	-2.436301184
P(T<=t) one-tail	0.011150007	0.05	Sig. Diff.
t Critical one-tail	1.708140745
P(T<=t) two-tail	0.022300015
t Critical two-tail	2.059538536

I believe both of these assignments follow the NETS-S standard #5. This standard discusses and includes research for educators and both of these assignments were  perfect examples of this.