4x^2-5x-14 is your answer :)
Answer:
A. whether a woman took hormones.
B. whether to woman in the study had a heart attack.
D. access to health care
Step-by-step explanation:
The study conducted to observe the menopausal woman must be supported with their health history. Some woman may have menopause at an early age while other go towards this at a later age. This can be due to smoking, hormone intake, severe diseases like heart attack or cancer and their routine health checkup details. There variables must be observed and included in experiment to reach a conclusion.
Answer:
?
Step-by-step explanation:
Answer:
Jenny save 4 times
for the month
Step-by-step explanation:
Given Jenny has saved
over the last 12 months.
She saved either
or
a month.
Let the number of months to save
be x
Let the number of months to save
be y
Total period is 12 month.

Jenny has saved $3,800 over the last 12 months.

Dividing both side from 50 we get,


Now Multiplying equation 1 by 5 we get,

Now Subtracting Equation 3 by equation 2 we get,

Substituting the value of y in equation 1 we get,

∴ Jenny save 4 Months of
and 8 Months of
in a 12 month duration
Answer:
a) 0.057
b) 0.5234
c) 0.4766
Step-by-step explanation:
a)
To find the p-value if the sample average is 185, we first compute the z-score associated to this value, we use the formula
where
N = size of the sample.
So,
As the sample suggests that the real mean could be greater than the established in the null hypothesis, then we are interested in the area under the normal curve to the right of 1.5811 and this would be your p-value.
We compute the area of the normal curve for values to the right of 1.5811 either with a table or with a computer and find that this area is equal to 0.0569 = 0.057 rounded to 3 decimals.
So the p-value is
b)
Since the z-score associated to an α value of 0.05 is 1.64 and the z-score of the alternative hypothesis is 1.5811 which is less than 1.64 (z critical), we cannot reject the null, so we are making a Type II error since 175 is not the true mean.
We can compute the probability of such an error following the next steps:
<u>Step 1
</u>
Compute
So <em>we would make a Type II error if our sample mean is less than 185.3721</em>.
<u>Step 2</u>
Compute the probability that your sample mean is less than 185.3711
So, <em>the probability of making a Type II error is 0.5234 = 52.34%
</em>
c)
<em>The power of a hypothesis test is 1 minus the probability of a Type II error</em>. So, the power of the test is
1 - 0.5234 = 0.4766