Could I please have assistance with a regression analysis questions? Greatly appreciate any sort of assistance. Below is the background and corresponding questions.

Marriage Satisfaction

Are marriages of people who met on line more or less likely to end in divorce? Are marriages of people who met on line happier or less happy?Recent research says that marriages of people who met on line are happier in their marriages, and their marriages last longer.

For instance, in 2012, some researchers asked a nationally representative sample of almost 20,000 people who married between 2005 and 2012 questions about a variety of things including: (1) questions on marital satisfaction that the authors combined into a Marriage Satisfaction Index^[1], and (2) how they met - online or not.They ran these regressions on the sample of 20,000 people (which includes both those who met on line and those who did not) where:

Marr-Satis: Marriage satisfaction, measured 1 through 7, with 1 being extremely unhappy and 7 being perfect.

Years-married: How many years it has been since the person was married (ranging from 0 for those married in 2012 to 7 for those married in 2005).

On-Line: A dummy variable =1 if the person met online (either at an online dating site, on a social networking site, or at some other site), 0 otherwise.

Regressions:(standard errors in parentheses)

(1) Marr-Satis = 5.040+ .188 On-Line+e

(.011)(.018)

Stdev .011=1.551

.011=x/141

(2) Marr-Satis = 5.203+ .0.105 On-Line - .036 Years-married +e

(.0203)(.0179)(.0039)

a)What is the average satisfaction of individuals who met their spouse on-line?

b)What is the average satisfaction of individuals who met their spouse off-line?

c)Are their satisfaction levels statistically different? Explain.

d)Imagine that the following regression was run instead of a.

Marr-Satis = b₀ + b₁ *Off-Line+e

What is the value of b₀ in the new regression?______________

What is the value of b₁ in the new regression?______________

e)Interpret the coefficient on Years Married in regression (2)

f)Interpret the coefficient on On-line in regression (2)