BADM 210 Final Exam Questions
with Complete Solutions
Central Limit Theorem - ANSWER-as sample size gets larger, the shape of the
sampling distribution will approach a normal distribution, regardless of the shape of
the original
Shape of t-dist relative to normal dist. - ANSWER-t-dist curve is slightly wider
low df (small sample size) = wider and shorter
high df ( large sample size) = taller and narrow
^ this occurs because difference between samp sd of xbar and pop sd of xbar
decreases
t in confidence intervals - ANSWER-t_(α/2) s/√n= t_(α/2) s_x ̅
sxbar = s/ sqrt n
confidence interval interpretation - ANSWER-"95% of the intervals formed will
include the population parameter"
"expect 90% of interval estimates to include pop parameter"
Alpha - ANSWER-significance level
prob of making a type I error
mu naught - ANSWER-constant threshold to be tested
Type I error - ANSWER-incorrectly reject Ho, and accept Ha
-rejection of a true null hypothesis
-related to alpha/sig level
-false positive
Type II error - ANSWER-incorrectly accept ho, when Ha is true
-failing to reject a false null hypothesis
-false negative
-usually related to not enough statistical power allowing us to conclude that we
should reject ho
with Complete Solutions
Central Limit Theorem - ANSWER-as sample size gets larger, the shape of the
sampling distribution will approach a normal distribution, regardless of the shape of
the original
Shape of t-dist relative to normal dist. - ANSWER-t-dist curve is slightly wider
low df (small sample size) = wider and shorter
high df ( large sample size) = taller and narrow
^ this occurs because difference between samp sd of xbar and pop sd of xbar
decreases
t in confidence intervals - ANSWER-t_(α/2) s/√n= t_(α/2) s_x ̅
sxbar = s/ sqrt n
confidence interval interpretation - ANSWER-"95% of the intervals formed will
include the population parameter"
"expect 90% of interval estimates to include pop parameter"
Alpha - ANSWER-significance level
prob of making a type I error
mu naught - ANSWER-constant threshold to be tested
Type I error - ANSWER-incorrectly reject Ho, and accept Ha
-rejection of a true null hypothesis
-related to alpha/sig level
-false positive
Type II error - ANSWER-incorrectly accept ho, when Ha is true
-failing to reject a false null hypothesis
-false negative
-usually related to not enough statistical power allowing us to conclude that we
should reject ho
