Linear Regression: Significance levels/Finding equation of fitted regression lines

I did an exam recently and I am looking for a solution to a question which no matter where I look, I can't find out how to do it. It doesn't help I'm not very good at stats hence the post here. Could someone maybe point out a Youtube video that deals with similar problems. It's specifically part (iii) and (iv) of the question below that I'm having difficulty with. Here's the Q.

Passive and active solar energy systems are becoming viable options to home builders as installation and operating costs decrease. Laminated solar modules utilise high-quality, single crystal silicon solar cells, connected electrically in series, to deliver a specified power output. Research was conducted to investigate the relationship between the solar cell temperature (°C) rise above ambient and the amount of insulation (megawatts per square centimetre). Data collected for nine solar cells sampled under identical experimental conditions are recorded in the table.

Temp rise above ambient Y 9 25 20 12 15 22 14 17 23
Insulation X 25 70 50 30 45 60 35 45 65

(i) Illustrate in a scatterplot (done this).
(ii) compute the coefficient of correlation and comment on its' value (done and got 96% r squared value so a strong correlation there).
(iii) Using a significance level of alpha = 5, test the claim that there is no linear correlation between the amount of insulation and the temperature rise above ambient (stuck on this, seems like a null hypothesis Q to me but a lot of this is new to me so I get confused easily).
(Iv) Find the equation of the fitted regression line and plot the regression line on the scatterplot. Interpret in your own words the equation of the fitted regression line (stick on this too).