STT 231 ACTUAL EXAM 2
QUESTIONS AND CORRECT
ANSWERS LATEST UPDATE
2026/2027 GRADED A+ .
, 1. what two conditions must be met in order for the CLT to apply for propor-tional testing?: 1: sample must be independent
and identically distributed; like random assignment/sam-pling
2: sample must be suflciently large
2. normal density curve: symmetric about the mean μ; has standard deviation σ; total area under the curve
= 1.0; values of the random variable X on x-axis; probabilities are represented by areas under the curve;
3. what do the numbers in the N(0,1) equation represent ✔✔ CORRECT ANSWER the first number is the mean (mu), and the second
is the SD (sigma)
4. what is the equation for a standard normal curve/distribution, and what do the axes represent ✔✔ CORRECT ANSWER
N(0,1) the x axis represents z-scores, and the y is the probability
5. what is the domain for a standard normal curve? which particu are we interested in ✔✔ CORRECT
ANSWER the actual domain=infinite, but we are interested mostly in (mu +
6. difference between pnorm and qnorm commands: pnorm: gives proportion/percent of data within the given range
qnorm: gives the cutott range for the percentile of data inputted
7. what are the required arguments for pnorm? qnorm ✔✔ CORRECT ANSWER pnorm(upper cutott, mean, SD) qnorm(upper
percentile cutott, mean, SD)
8. when do you use the lower.tail=false argument ✔✔ CORRECT ANSWER during p/qnorm commands, when you are interested in
the right side distribution
9. normal model for sampling distribution of pi hat: still follows the rule of standard normal curve (N(0,1)), but it uses N(pi, SE equation) because
10. what is standard error? how do you interpret the results ✔✔ CORRECT ANSWER it measures how close the current sample
data reflects the overall population predicted data, a high standard error value represents that your sample is not very reflective of the population and is very spread out, vice
versa for low
11. how do SE and sample size n relate ✔✔ CORRECT ANSWER as n increases, SE decreases, inverse relationship.
12. normal model for a sampling distribution of x bar: still N(0,1) template, but the mean is represented by mu, and the SD is sigma/square root
of n
13. when should you use normal model sampling distribution of x bar and when for pi hat ✔✔ CORRECT ANSWER
x bar if you are given mu in the problem, pi hat if you are given pi in the problem
QUESTIONS AND CORRECT
ANSWERS LATEST UPDATE
2026/2027 GRADED A+ .
, 1. what two conditions must be met in order for the CLT to apply for propor-tional testing?: 1: sample must be independent
and identically distributed; like random assignment/sam-pling
2: sample must be suflciently large
2. normal density curve: symmetric about the mean μ; has standard deviation σ; total area under the curve
= 1.0; values of the random variable X on x-axis; probabilities are represented by areas under the curve;
3. what do the numbers in the N(0,1) equation represent ✔✔ CORRECT ANSWER the first number is the mean (mu), and the second
is the SD (sigma)
4. what is the equation for a standard normal curve/distribution, and what do the axes represent ✔✔ CORRECT ANSWER
N(0,1) the x axis represents z-scores, and the y is the probability
5. what is the domain for a standard normal curve? which particu are we interested in ✔✔ CORRECT
ANSWER the actual domain=infinite, but we are interested mostly in (mu +
6. difference between pnorm and qnorm commands: pnorm: gives proportion/percent of data within the given range
qnorm: gives the cutott range for the percentile of data inputted
7. what are the required arguments for pnorm? qnorm ✔✔ CORRECT ANSWER pnorm(upper cutott, mean, SD) qnorm(upper
percentile cutott, mean, SD)
8. when do you use the lower.tail=false argument ✔✔ CORRECT ANSWER during p/qnorm commands, when you are interested in
the right side distribution
9. normal model for sampling distribution of pi hat: still follows the rule of standard normal curve (N(0,1)), but it uses N(pi, SE equation) because
10. what is standard error? how do you interpret the results ✔✔ CORRECT ANSWER it measures how close the current sample
data reflects the overall population predicted data, a high standard error value represents that your sample is not very reflective of the population and is very spread out, vice
versa for low
11. how do SE and sample size n relate ✔✔ CORRECT ANSWER as n increases, SE decreases, inverse relationship.
12. normal model for a sampling distribution of x bar: still N(0,1) template, but the mean is represented by mu, and the SD is sigma/square root
of n
13. when should you use normal model sampling distribution of x bar and when for pi hat ✔✔ CORRECT ANSWER
x bar if you are given mu in the problem, pi hat if you are given pi in the problem
