[Solved]-Q2 Q1 Actually Use Mc Compute 1o X Da S Probability Density Function Standard Normal Set S Q37211181

Please use R programming to solve. I included question 1 forreference. Please answer question 2.

Q2. In Q1, we actually use MC to compute -1o(x)da, where ф(-) İs the probability density function of the standard normal. Now, set sample size n-10, 000 and random seed 268. Use MC method to compte (x)da, where f( is the probability density function of normal distribution with mean 4 and variance 3. Write down a single R expression for this (not including set random seed and generate random numbers). Use the function pnorm() for a check. Q1. Monte Carlo method (MC) provides a numeric approximation to find the probability of absolute value of a standard normal random variable less than 1, ie. P(Z < 1), where Z~N(0, 1). To do so, one may first generate 10, 000 random numbers from N(0,1) and then compute the proportion of the numbers that have absolute value less than 1. Code your own script for MC method to estimate P( with that by the function pnorm) < 1) and compare your result Show transcribed image text Q2. In Q1, we actually use MC to compute -1o(x)da, where ф(-) İs the probability density function of the standard normal. Now, set sample size n-10, 000 and random seed 268. Use MC method to compte (x)da, where f( is the probability density function of normal distribution with mean 4 and variance 3. Write down a single R expression for this (not including set random seed and generate random numbers). Use the function pnorm() for a check.
Q1. Monte Carlo method (MC) provides a numeric approximation to find the probability of absolute value of a standard normal random variable less than 1, ie. P(Z

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Answer to Q2. In Q1, we actually use MC to compute -1o(x)da, where ф(-) İs the probability density function of the standard norm… . . .