Answer:
Step-by-step explanation:
Hello,
step 1 - we divide all terms by 2
step 2 - we complete the square
we can notice that
so
step 3 - we move the constant term to the right of the equation
step 4 - we take the square root on both sides of the equation
or
step 5 - we subtract 2 from both sides
or
so the solutions are 0.12 and -4.12
hope this helps
Answer:
The estimated standard error for the sampling distribution of differences in sample proportions is 0.0382.
Step-by-step explanation:
To solve this question, we need to understand the Central Limit Theorem and subtraction of normal variables.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean and standard deviation
Subtraction of normal variables:
When we subtract normal variables, the mean is the subtraction of the means, while the standard error is the square root of the sum of the variances:
Of the 193 smokers taking a placebo, 29 stopped smoking by the 8th day.
This means that:
Of the 266 smokers taking only the antidepressant buproprion, 82 stopped smoking by the 8th day.
This means that:
Calculate the estimated standard error for the sampling distribution of differences in sample proportions.
The estimated standard error for the sampling distribution of differences in sample proportions is 0.0382.