lease sqs regression and more

I need some help this one! I am stumped!

In the hope of preventing ecological damage from oil spills, a biochemical company is developing an
enzyme to break up oil into less harmful chemicals. The table below shows the time it took for the enzyme
to break up oil samples at different temperatures. The researcher plans to use these data in a regression
analysis for predicting the time to break up from the oil temperature.
Observation
Number 1 2 3 4 5 6
Oil
Temperature
(0C) 3 10 15 21 33 37
Time to
Break up
(seconds) 165 98 65 62 26 9
a) Calculate the equation of the least squares regression line. Use 'Oil Temperature' as the
explanatory variable.
b) Plot the data and the least squares regression line.
c) Find and interpret the correlation coefficient.
d) Find and interpret the coefficient of determination.
e) Draw the residual plot for these data. Based on the residual plot, is a linear model
appropriate for these data.
f) Using real world terms like oil temperature and time to breakup, interpret the meaning of
the y-intercept of the least squares regression line that you found in part a).
g) Using real world terms, like oil temperature and time to breakup, interpret the meaning
of the slope of the least squares regression line that you found in part a)
h) The average annual water temperature in Alaskan waters is 04C. How long would the
enzyme take to break up oil under these circumstances?
h) The company claims that even when the water temperatures are as low as -50C, the
enzyme will break up the oil in less than 3 minutes. Briefly comment on the validity of
this claim.

These are fairly straightforward computational tasks. At which point of which part are you having difficulty?

Please be specific. Thank you!