NEW STT 231 EXAM 2 QUESTIONS AND CORRECT ANSWERS 100%
VERIFIED!!!! ALREADY GRADED A+
what two conditions must be met in order for the CLT to apply for proportional testing? - (answer)1:
sample must be independent and identically distributed; like random assignment/sampling
2: sample must be sufficiently large
normal density curve - (answer)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;
what do the numbers in the N(0,1) equation represent? - (answer)the first number is the mean (mu), and
the second is the SD (sigma)
what is the equation for a standard normal curve/distribution, and what do the axes represent? -
(answer)N(0,1) the x axis represents z-scores, and the y is the probability
what is the domain for a standard normal curve? which particular interval are we interested in? -
(answer)the actual domain=infinite, but we are interested mostly in (mu +/- 3sigma)
difference between pnorm and qnorm commands - (answer)pnorm: gives proportion/percent of data
within the given range
qnorm: gives the cutoff range for the percentile of data inputted
what are the required arguments for pnorm? qnorm? - (answer)pnorm(upper cutoff, mean, SD)
qnorm(upper percentile cutoff, mean, SD)
when do you use the lower.tail=false argument? - (answer)during p/qnorm commands, when you are
interested in the right side distribution
normal model for sampling distribution of pi hat - (answer)still follows the rule of standard normal curve
(N(0,1)), but it uses N(pi, SE equation) because
, NEW STT 231 EXAM 2 QUESTIONS AND CORRECT ANSWERS 100%
VERIFIED!!!! ALREADY GRADED A+
what is standard error? how do you interpret the results? - (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
how do SE and sample size n relate? - (answer)as n increases, SE decreases, inverse relationship.
normal model for a sampling distribution of x bar - (answer)still N(0,1) template, but the mean is
represented by mu, and the SD is sigma/square root of n
when should you use normal model sampling distribution of x bar and when for pi hat? - (answer)x bar if
you are given mu in the problem, pi hat if you are given pi in the problem
if you are given a problem that gives the sample mean and asks for the proportion greater than or equal
to a z score, what would you do? - (answer)set up the equation with the pnorm command using the
standard normal model, with pnorm(the value,0,1)
how do you create a qqplot in R? - (answer)two commands required:
1: qqnorm(data set$variable)
2: qqline(data set$variable)
what would a straight qq plot indicate? - (answer)the sample data can be represented by a normal
distribution model (unimodal, no skew, centered at the mean)
what would a concave up qq plot indicate? - (answer)right-skewed data
what would a concave down qq plot indicate? - (answer)the data is skewed/tailed to the left
what does an s shaped qq plot represent? - (answer)a plot that looks normally distributed but the tails
are either too fat/too thin (granularity differences) with few outliers
VERIFIED!!!! ALREADY GRADED A+
what two conditions must be met in order for the CLT to apply for proportional testing? - (answer)1:
sample must be independent and identically distributed; like random assignment/sampling
2: sample must be sufficiently large
normal density curve - (answer)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;
what do the numbers in the N(0,1) equation represent? - (answer)the first number is the mean (mu), and
the second is the SD (sigma)
what is the equation for a standard normal curve/distribution, and what do the axes represent? -
(answer)N(0,1) the x axis represents z-scores, and the y is the probability
what is the domain for a standard normal curve? which particular interval are we interested in? -
(answer)the actual domain=infinite, but we are interested mostly in (mu +/- 3sigma)
difference between pnorm and qnorm commands - (answer)pnorm: gives proportion/percent of data
within the given range
qnorm: gives the cutoff range for the percentile of data inputted
what are the required arguments for pnorm? qnorm? - (answer)pnorm(upper cutoff, mean, SD)
qnorm(upper percentile cutoff, mean, SD)
when do you use the lower.tail=false argument? - (answer)during p/qnorm commands, when you are
interested in the right side distribution
normal model for sampling distribution of pi hat - (answer)still follows the rule of standard normal curve
(N(0,1)), but it uses N(pi, SE equation) because
, NEW STT 231 EXAM 2 QUESTIONS AND CORRECT ANSWERS 100%
VERIFIED!!!! ALREADY GRADED A+
what is standard error? how do you interpret the results? - (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
how do SE and sample size n relate? - (answer)as n increases, SE decreases, inverse relationship.
normal model for a sampling distribution of x bar - (answer)still N(0,1) template, but the mean is
represented by mu, and the SD is sigma/square root of n
when should you use normal model sampling distribution of x bar and when for pi hat? - (answer)x bar if
you are given mu in the problem, pi hat if you are given pi in the problem
if you are given a problem that gives the sample mean and asks for the proportion greater than or equal
to a z score, what would you do? - (answer)set up the equation with the pnorm command using the
standard normal model, with pnorm(the value,0,1)
how do you create a qqplot in R? - (answer)two commands required:
1: qqnorm(data set$variable)
2: qqline(data set$variable)
what would a straight qq plot indicate? - (answer)the sample data can be represented by a normal
distribution model (unimodal, no skew, centered at the mean)
what would a concave up qq plot indicate? - (answer)right-skewed data
what would a concave down qq plot indicate? - (answer)the data is skewed/tailed to the left
what does an s shaped qq plot represent? - (answer)a plot that looks normally distributed but the tails
are either too fat/too thin (granularity differences) with few outliers
