The data below shows a comparison of the median hourly wage and the number of marriages. Does making more money cause more people to get married or less? Use the statcrunch data to answer the questions below:

Dependent Variable: # of Marriages Independent Variable: Median Hourly Wages (in dollars) Sample size: 30 R (correlation coefficient) = -0.88869237 R-sq = 0.78977413 Estimate of error standard deviation: 52872.112

Parameter	Estimate	Std. Err.	Alternative	DF	T-Stat	P-value
Intercept	2660025.4	38676.282	0	28	68.776658	<0.0001
Slope	-25722.242	2507.9647	0	28	-10.256222	<0.0001

Is there a correlation between Median Hourly Wages and # of Marriages?

a) What would be the appropriate null hypothesis for this scenario? [ Select ] ["Wages and # of Marriages are not correlated.", "There is a positive linear relationship between Wages and # of Marriages.", "Wages and # of Marriages are correlated."]

b) What would be the appropriate alternative hypothesis? [ Select ] ["Wages and # of Marriages are Independent.", "Wages and # of Marriages are correlated.", "Wages and # of Marriages are not correlated."]

c) Pearson's correlation coefficient (r) tells us that a [ Select ] ["strong", "weak"] [ Select ] ["positive", "negative"] correlation exists between Median Hourly Wages and # of Marriages.

d) The coefficient of determination tells us that about [ Select ] ["89", "79", "99"] % of the variation in [ Select ] ["# of marriages", "median hourly wages"] can be explained by the variation in [ Select ] ["# of marriages", "median hourly wages"] and [ Select ] ["1", "11", "21"] % is unexplained or due to error.

e. For the data found in the previous question, what is the point estimate that would be used in prediction or estimation for an hourly wage of $16? Round this value to the nearest whole number.