BUAL 2650 AUBURN EXAM 1 QUESTIONS AND ALL
ANSWERS CORRECT
sample proportion: We use the ANSWER sample of the population, p-hat,
because we do not know the parameter of the entire population, p. p=p-hat most
of the time, but not always.
The standard deviation is the average difference between p and p-hat. The
estimate of p-hat is usually off by the sq.rt of pq/n since the proportion from the
sample, p-hat, does not equal p.
Confidence interval: Assuming symmetry, the answer is p-hat +/- 2*SD(p-hat)
for a 95% confidence interval, meaning that 95/100 will include p.
ANSWER randomization condition, 10% condition (no more than 10% of the
population), and success/failure (nq >10, np >10) are the conditions to verify.
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)
(p-3sq.rt.pq/n,p+3sq.rt.pq/n) = 99.7%
z-score; ANSWER p-hat; p/SD(p-hat); mu(0,1) standard normal distribution
A positive z-score indicates an uncommon ANSWER outlier > 3.
A negative z-score indicates an unexpected ANSWER outlier of less than -3.
Null hypothesis: ANSWER: Until someone is proven guilty, we assume they
are innocent. We hold onto the hypothesis until the evidence makes it
improbable beyond a reasonable doubt. We also take into account whether the
data supports the hypothesis.
Stat hypothesis testing: ANSWER the population perimeter is the original
hypothesis, p=x; gather information to refute the hypothesis, create p-hat, and
determine whether the information is likely or unlikely.
Ho stands for population parameter, null hypothesis, and hypothesized value.
ANSWERS CORRECT
sample proportion: We use the ANSWER sample of the population, p-hat,
because we do not know the parameter of the entire population, p. p=p-hat most
of the time, but not always.
The standard deviation is the average difference between p and p-hat. The
estimate of p-hat is usually off by the sq.rt of pq/n since the proportion from the
sample, p-hat, does not equal p.
Confidence interval: Assuming symmetry, the answer is p-hat +/- 2*SD(p-hat)
for a 95% confidence interval, meaning that 95/100 will include p.
ANSWER randomization condition, 10% condition (no more than 10% of the
population), and success/failure (nq >10, np >10) are the conditions to verify.
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)
(p-3sq.rt.pq/n,p+3sq.rt.pq/n) = 99.7%
z-score; ANSWER p-hat; p/SD(p-hat); mu(0,1) standard normal distribution
A positive z-score indicates an uncommon ANSWER outlier > 3.
A negative z-score indicates an unexpected ANSWER outlier of less than -3.
Null hypothesis: ANSWER: Until someone is proven guilty, we assume they
are innocent. We hold onto the hypothesis until the evidence makes it
improbable beyond a reasonable doubt. We also take into account whether the
data supports the hypothesis.
Stat hypothesis testing: ANSWER the population perimeter is the original
hypothesis, p=x; gather information to refute the hypothesis, create p-hat, and
determine whether the information is likely or unlikely.
Ho stands for population parameter, null hypothesis, and hypothesized value.
