BUAL 2650 Auburn Exam 1 Questions &
Answers 2024/2025
sample proportion - ANSWERSsample of the population, p-hat, that we use because we do not know the
parameter of the whole population, p. p=p-hat most of the time but not always
standard deviation - ANSWERStypical difference between p and p-hat. the proportion from sample, p-
hat, is not equal to p, typically the estimate p-hat will be off by the sq.rt of pq/n,
confidence interval - ANSWERSassume symmetry, p-hat +/- 2*SD(p-hat) for 95% confidence interval, so
95/100 will contain p.
conditions to check - ANSWERSrandomization condition, 10% condition (no larger than 10% of the
population), success/failure (nq >10, np>10)
confidence intervals for proportions - ANSWERS68%- (p-sq.rt.pq/n,p+sq.rt.pq/n)
95%- (p-2sq.rt.pq/n,p+2sq.rt.pq/n)
99.7%- (p-3sq.rt.pq/n,p+3sq.rt.pq/n)
z-score - ANSWERSp-hat - p / SD(p-hat)
mu(0,1) standard normal distribution
positive z-score - ANSWERSoutlier > 3 is unusual
negative z-score - ANSWERSoutlier < -3 is unusual
null hypothesis - ANSWERSwe assume someone is innocent until proven guilty, retain the hypothesis
until the facts make it unlikely beyond a reasonable doubt, consider if the data is consistent with the
hypothesis
, stat hypothesis testing - ANSWERSthe population perimeter is the initial hypothesis, p=x, collect data to
challenge the hypothesis and form p-hat, then decide if the data proves likely or unlikely
Ho - ANSWERSnull hypothesis, population parameter, hypothesized value
Ha - ANSWERSalternative hypothesis, the parameter we deem plausible when we reject the null
hypothesis
Two-sided test - ANSWERSpopulation parameter does not equal hypothesized value
One-sided test - ANSWERSpopulation paramater > or < hypothesized value
Reject the null - ANSWERSless than 0.05, small
Fail to reject the null, accept the null - ANSWERSmore than 0.05, large
conclusion - ANSWERSstatement about if we reject or fail to reject the null hypothesis
p-value - ANSWERSprobability of deviating in either direction from the hypothesized value
central limit theorem - ANSWERSwhen we sample at random, the proportion (p-hat) we will get varying
from sample to sample because of point estimates
bell-shaped model - ANSWERSnormal distribution sample size gets larger and each sample average tends
to become closer to the population mean and approach the normal model
CLT sampling distribution - ANSWERSof any mean becomes normal as the sample size grows regardless
of the shape of the population distribution
Answers 2024/2025
sample proportion - ANSWERSsample of the population, p-hat, that we use because we do not know the
parameter of the whole population, p. p=p-hat most of the time but not always
standard deviation - ANSWERStypical difference between p and p-hat. the proportion from sample, p-
hat, is not equal to p, typically the estimate p-hat will be off by the sq.rt of pq/n,
confidence interval - ANSWERSassume symmetry, p-hat +/- 2*SD(p-hat) for 95% confidence interval, so
95/100 will contain p.
conditions to check - ANSWERSrandomization condition, 10% condition (no larger than 10% of the
population), success/failure (nq >10, np>10)
confidence intervals for proportions - ANSWERS68%- (p-sq.rt.pq/n,p+sq.rt.pq/n)
95%- (p-2sq.rt.pq/n,p+2sq.rt.pq/n)
99.7%- (p-3sq.rt.pq/n,p+3sq.rt.pq/n)
z-score - ANSWERSp-hat - p / SD(p-hat)
mu(0,1) standard normal distribution
positive z-score - ANSWERSoutlier > 3 is unusual
negative z-score - ANSWERSoutlier < -3 is unusual
null hypothesis - ANSWERSwe assume someone is innocent until proven guilty, retain the hypothesis
until the facts make it unlikely beyond a reasonable doubt, consider if the data is consistent with the
hypothesis
, stat hypothesis testing - ANSWERSthe population perimeter is the initial hypothesis, p=x, collect data to
challenge the hypothesis and form p-hat, then decide if the data proves likely or unlikely
Ho - ANSWERSnull hypothesis, population parameter, hypothesized value
Ha - ANSWERSalternative hypothesis, the parameter we deem plausible when we reject the null
hypothesis
Two-sided test - ANSWERSpopulation parameter does not equal hypothesized value
One-sided test - ANSWERSpopulation paramater > or < hypothesized value
Reject the null - ANSWERSless than 0.05, small
Fail to reject the null, accept the null - ANSWERSmore than 0.05, large
conclusion - ANSWERSstatement about if we reject or fail to reject the null hypothesis
p-value - ANSWERSprobability of deviating in either direction from the hypothesized value
central limit theorem - ANSWERSwhen we sample at random, the proportion (p-hat) we will get varying
from sample to sample because of point estimates
bell-shaped model - ANSWERSnormal distribution sample size gets larger and each sample average tends
to become closer to the population mean and approach the normal model
CLT sampling distribution - ANSWERSof any mean becomes normal as the sample size grows regardless
of the shape of the population distribution
