MGSC 291 Exam 3 Study Guide Exam
Questions and Answers Graded A+
Uncertainty quantification - Correct answer-tools needed to be able to quantify the
uncertainty in our point estimates
goal with statistical analysis: not to eliminate uncertainty, but to REDUCE and
QUANTIFY it
Frequentist approach - Correct answer-Repeatedly drawing samples of data and
counting the frequency with which an event happens
Frequency - Correct answer-mean of the sample
Sampling variability - Correct answer-Frequency values(different sample means)
are calculated, and varies from sample to sample
Sampling distribution of sample means - Correct answer-The distribution of all
possible sample means(frequencies) of size n from the same population
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,How is the frequentist approach different from bootstrapping? - Correct answer-
Different from bootstrapping because bootstrapping resamples the original sample
of data
SHAPE of the sampling distribution of a sample mean - Correct answer-normal
(if we take large samples OR we sample from a normal distribution)
CENTER of the sampling distribution of a sample mean - Correct answer-(greek
mu symbol) --- our average or our mean
Parameter = mu ; (true mean of the population) the value is fixed but unknown
Standard error(variability) - Correct answer-Measures how much sample statistics
vary from the population parameter(mu) ; how far a sample statistic is likely to fall
from population parameter
How do we calculate standard error of the mean - Correct answer-Using the
standard deviation of the sampling distribution
formula: standard deviation / sqrt(n)
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, Standard deviation - Correct answer-how spread out the values are ; how far data is
likely to fall from the mean
Estimating a regression coefficient - Correct answer-ex:betastats["Estimate"]+c(-
1.96,1.96)*betastats["Std. Error"]
point estimate + C*se
we are 95% confident that CPO cars have a higher price than uncertified by AT
LEAST xxx and AT MOST xxxx
Standard error when using the bootstrapping method - Correct answer-estimates
the sampling distribution for your estimator of interest (even if derived from an
incorrect model)
ex: R
sd(muhats)
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Questions and Answers Graded A+
Uncertainty quantification - Correct answer-tools needed to be able to quantify the
uncertainty in our point estimates
goal with statistical analysis: not to eliminate uncertainty, but to REDUCE and
QUANTIFY it
Frequentist approach - Correct answer-Repeatedly drawing samples of data and
counting the frequency with which an event happens
Frequency - Correct answer-mean of the sample
Sampling variability - Correct answer-Frequency values(different sample means)
are calculated, and varies from sample to sample
Sampling distribution of sample means - Correct answer-The distribution of all
possible sample means(frequencies) of size n from the same population
©COPYRIGHT 2025, ALL RIGHTS RESERVED 1
,How is the frequentist approach different from bootstrapping? - Correct answer-
Different from bootstrapping because bootstrapping resamples the original sample
of data
SHAPE of the sampling distribution of a sample mean - Correct answer-normal
(if we take large samples OR we sample from a normal distribution)
CENTER of the sampling distribution of a sample mean - Correct answer-(greek
mu symbol) --- our average or our mean
Parameter = mu ; (true mean of the population) the value is fixed but unknown
Standard error(variability) - Correct answer-Measures how much sample statistics
vary from the population parameter(mu) ; how far a sample statistic is likely to fall
from population parameter
How do we calculate standard error of the mean - Correct answer-Using the
standard deviation of the sampling distribution
formula: standard deviation / sqrt(n)
©COPYRIGHT 2025, ALL RIGHTS RESERVED 2
, Standard deviation - Correct answer-how spread out the values are ; how far data is
likely to fall from the mean
Estimating a regression coefficient - Correct answer-ex:betastats["Estimate"]+c(-
1.96,1.96)*betastats["Std. Error"]
point estimate + C*se
we are 95% confident that CPO cars have a higher price than uncertified by AT
LEAST xxx and AT MOST xxxx
Standard error when using the bootstrapping method - Correct answer-estimates
the sampling distribution for your estimator of interest (even if derived from an
incorrect model)
ex: R
sd(muhats)
©COPYRIGHT 2025, ALL RIGHTS RESERVED 3
