Kelly uses her credit card to purchase a new television for $489.25. She can pay off up to $225 per month. The card has an annua
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Since we are not given any information about the proportion, we will assume the sample proportion to be 0.50
so,
p = 0.50
The Error is 10% percentage point. This means that on either side of the population proportion the error is 5% so E = 0.05
z = 1.645 (Z value for 90% confidence interval)
The margin of error for population proportion is calculated as:
This means 271 students should be included in the sample
so,
p = 0.50
The Error is 10% percentage point. This means that on either side of the population proportion the error is 5% so E = 0.05
z = 1.645 (Z value for 90% confidence interval)
The margin of error for population proportion is calculated as:
This means 271 students should be included in the sample
Answer:
Below is the procedure that was used to find the answer.
Step-by-step explanation:
Let be "e" the weight in pounds of the elephant and "c" the weight in pounds of the cat.
According to the information provided in the exercise, we know that The weight of an elephant is times the weight of a cat. Based on this we can write the following equation:
If the weight in pounds of the elephant is:
We must substitute this value into the equation and then solve for "c" in order to find the weight in pounds of the cat.
Then we get:
Answer:
Step-by-step explanation:
For this case we have a sample size of n = 250 units and in this sample they found that 24 units failed one or more of the tests.
We are interested in the proportion of units that fail to meet the company's specifications, and we can estimate this with:
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The confidence interval for a proportion is given by this formula
For the 98% confidence interval the value of and
, with that value we can find the quantile required for the interval in the normal standard distribution.
And the margin of error would be: