need help plz

i know the answers for part(a) and part(b) and don't show me the answers for part(a) and part(b)

i just need help in part(c) and part(d) plz

Problem 2: Discrete Approximation In continuous probability, we often need to solve messy integrals. For example, in this class we might need to use integrals to cvaluate the probability of an event under a cumilative distribution function (CDF). Rather than solve this by hand, we can approximate it using discrete intervals, This problem will explon discrete approximation of integrals using a Gaussian model. Recall that tlie probability density function of a Gamsian is, N(x,2)=221exp(221(x)2). In tho questions below. we will use Pytlion to form a diserete approximation of this continuous distribution, and evaluate associated probabilities. a) Form a discrete approximation of the Normal PDF with mean =70 and standard deviation =2. To do this, create an array of evenly spaced values in the range {68,76} at increments of 2 excluding 76 (this array will include 68 and 74 ). The fumetion numpy arange might be helpful. Greate an array p containing vulues of the PDF at each location x. Plot the resalt as a bar chart (use matplotis. pyplot.bar). In the same figure, overlay a PDF curve (use natplotl ib.pyplot.plot) at more finely spaced intervals (eg 0.01). Paste your code here. b) The bar chart above is a diserete approxination of the continuous PDF. We will uise it to approximate P(68