Answer:
The 95% confidence interval estimate of the true population proportion of U.S. employers that were likely to require higher employee contributions for health care coverage is 0.52 +/- 0.0370
= (0.4830, 0.5570)
The margin of error M.E = 0.0370
Step-by-step explanation:
Confidence interval can be defined as a range of values so defined that there is a specified probability that the value of a parameter lies within it.
The confidence interval of a statistical data can be written as.
p+/-z√(p(1-p)/n)
p+/-M.E
Given that;
M.E = margin of error
Proportion p = 52% = 0.52
Number of samples n = 700
Confidence interval = 95%
z value (at 95% confidence) = 1.96
Substituting the values we have;
0.52 +/- 1.96√(0.52(1-0.52)/700)
0.52 +/- 1.96(0.0189)
0.52 +/- 0.0370
( 0.4830, 0.5570)
The 95% confidence interval estimate of the true population proportion of U.S. employers that were likely to require higher employee contributions for health care coverage is 0.52 +/- 0.0370
= (0.4830, 0.5570)
The margin of error M.E = 0.0370
She didn't make any mistake
Answer:
Prob ( 41 <= X <= 77) =
Prob ( (41-59)/9 <= Z <= (77-59)/9 ) = <--- changes to z scores
Prob ( -18/9 <= Z <= 18/9 ) =
Prob ( -2 <= Z <= 2) =
Prob ( z<=2) - Prob(Z<=-2) = <--- by property of the normal bell curve
= 0.9772 - 0.0228 <--- per the normal distribution table
= 0.9544
Step-by-step explanation:
make sense ?
it is 1/6 that is the anwser
Answer:
There is no "next number"
I think.
Step-by-step explanation:
