a)
From a standard normal distribution table we have that:

b)
In this case we need to use the z-score defined as:

where mu is the mean, sigma is the standard deviation and x is the value we are looking for; in this case we would have:

Therefore:

c)
Using the method in the previous part and the probability properties we have:
![\begin{gathered} P(71d)<p>To find how many teams we find the probability and multiply by the population:</p>[tex]\begin{gathered} 30P(X>76)=30P(z>(76-89)/(11)) \\ =30P(z>-1.1818) \\ =30(0.8183) \\ =24.54 \end{gathered}]()
Therefore approximately 25 teams have at least 76 points.