BUAL 2650 AUBURN EXAM 1 STUDY GUIDE
sample proportion - Answer -sample 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 - Answer -typical 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 - Answer -assume symmetry, p-hat +/- 2*SD(p-hat) for 95%
confidence interval, so 95/100 will contain p.
conditions to check - Answer -randomization condition, 10% condition (no larger than
10% of the population), success/failure (nq >10, np>10)
confidence intervals for proportions - Answer -68%- (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 - Answer -p-hat - p / SD(p-hat)
mu(0,1) standard normal distribution
positive z-score - Answer -outlier > 3 is unusual
negative z-score - Answer -outlier < -3 is unusual
null hypothesis - Answer -we 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 - Answer -the 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 - Answer -null hypothesis, population parameter, hypothesized value
Ha - Answer -alternative hypothesis, the parameter we deem plausible when we reject
the null hypothesis
Two-sided test - Answer -population parameter does not equal hypothesized value
One-sided test - Answer -population paramater > or < hypothesized value
sample proportion - Answer -sample 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 - Answer -typical 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 - Answer -assume symmetry, p-hat +/- 2*SD(p-hat) for 95%
confidence interval, so 95/100 will contain p.
conditions to check - Answer -randomization condition, 10% condition (no larger than
10% of the population), success/failure (nq >10, np>10)
confidence intervals for proportions - Answer -68%- (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 - Answer -p-hat - p / SD(p-hat)
mu(0,1) standard normal distribution
positive z-score - Answer -outlier > 3 is unusual
negative z-score - Answer -outlier < -3 is unusual
null hypothesis - Answer -we 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 - Answer -the 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 - Answer -null hypothesis, population parameter, hypothesized value
Ha - Answer -alternative hypothesis, the parameter we deem plausible when we reject
the null hypothesis
Two-sided test - Answer -population parameter does not equal hypothesized value
One-sided test - Answer -population paramater > or < hypothesized value
