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Example Questions
Example Question #61 : Ap Statistics
Which of the following statements are correct about confidence intervals?
The width of a confidence interval does not change as the sample size increases and increases as the confidence level increases.
The width of a confidence interval decreases as the sample size increases and increases as the confidence level increases.
The width of a confidence interval decreases as the sample size increases and increases as the confidence level decreases.
The width of a confidence interval increases as the sample size increases and increases as the confidence level decreases.
The width of a confidence interval increases as the sample size increases and increases as the confidence level increases.
The width of a confidence interval decreases as the sample size increases and increases as the confidence level increases.
Larger samples give narrower intervals. We are able to estimate a population proportion more precisely with a larger sample size.
As the confidence level increases the width of the confidence interval also increases. A larger confidence level increases the chance that the correct value will be found in the confidence interval. This means that the interval is larger.
Example Question #62 : Ap Statistics
You are asked to create a 
Keep in mind that the margin of error for a confidence interval based on a normal population is equal to 
From the problem, we can tell that 
The minimum sample size is 
Example Question #61 : Ap Statistics
Jim calculated a 
More information is needed.
There is a 
In the long run, 
In the long run,
95% confidence means that the methods Jim uses to calculate his confidence interval give him correct results 95% of the time. It does not mean that there is a 95% chance that the true mean will be inside the interval. It also does not mean that 95% of all heights or possible sample means fall within the interval.
Example Question #2 : Confidence Intervals And Regression
The number of hamburgers served by McGregors per day is normally distributed and has a mean of 
First, find the first quartile of the distribution.
Then, find the third quartile of the distribution.
Example Question #1 : How To Use The Addition Rule
The probability that it will rain today is 0.35. What is the probability that it will not rain?
The answer is 0.65 because Pr(~Rain) is the complement of Pr(Rain) and both events are mutually exclusive.
When two events are mutually exclusive, 
Example Question #2 : How To Use The Addition Rule
Assume there is an election involving three parties: D, R, and I. The probability of D winning is .11, R winning is .78, and I winning is .11. What is the probability of D or R winning?
1
.78
0
.89
.89
Since all of the events are mutually exclusive (one of the parties must win), you can get the probability of either D or R winning by adding their probabilities.
Since the probability of D winning is .11 and R winning is .78, the probability of D or R winning is .89.
Example Question #62 : Ap Statistics
If 1 card is chosen at random from a deck of cards, what is the probability that it will be a heart or a king?
17/52
29/52
13/52
26/52
4/13
4/13
In a deck of cards, there are 52 total cards, 13 hearts, 4 kings, and 1 king that is a heart.
So,
Example Question #61 : Ap Statistics
Using a standard deck of cards, what is the probability of choosing a single face card?
There are 
Thus the probability of choosing a single face card is 
Example Question #62 : Ap Statistics
A student randomly selected a highlighter from her desk. There were five highlighters on the desk, each of a different color--blue, green, yellow, red, and orange. What is the probability that the student selected either the red or the yellow highlighter?
In this case, we want to know the probability of multiple, mutually exclusive possible outcomes. To determine the probability of the two possible outcomes, simply add them together. This is called the addition rule.
Example Question #64 : Ap Statistics
What is the probability of obtaining at most 
First find the number of ways to get 0, 1, or 2 heads.
Remember, 
Now combine these to find the probability of seeing at most 2 heads in 10 coin tosses:
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