0
Confidence interval (CI) is a parameter with a degree of confidence. Thus, 95 % CI means parameter with 95 % of confidence level. The most commonly used is 95 % confidence interval.
Confidence intervals for means and proportions are calculated as follows:
point estimate ± margin of error.
Add your answer:
Earn +20 pts
What is the Z value for 95 percent confidence interval estimation?
1.96
When the sample size and sample standard deviation remain the same a 99 percent confidence interval for a population mean will be narrower than the 95 percent confidence interval for the mean?
Never!
When the sample size increase what will happen to the 95 percent confidence interval?
It becomes narrower.
Does the confidence interval always contain the true population parameter?
No, the confidence interval (CI) doesn't always contain the true population parameter. A 95% CI means that there is a 95% probability that the population parameter falls within the specified CI.
What does 95 percent confidence interval mean?
You construct a 95% confidence interval for a parameter such as mean, variance etc. It is an interval in which you are 95 % certain (there is a 95 % probability) that the true unknown parameter lies. The concept of a 95% Confidence Interval (95% CI) is one that is somewhat elusive. This is primarily due to the fact that many students of statistics are simply required to memorize its definition without fully understanding its implications. Here we will try to cover both the definition as well as what the definition actually implies. The definition that students are required to memorize is: If the procedure for computing a 95% confidence interval is used over and over, 95% of the time the interval will contain the true parameter value. Students are then told that this definition does not mean that an interval has a 95% chance of containing the true parameter value. The reason that this is true, is because a 95% confidence interval will either contain the true parameter value of interest or it will not (thus, the probability of containing the true value is either 1 or 0). However, you have a 95% chance of creating one that does. In other words, this is similar to saying, "you have a 50% of getting a heads in a coin toss, however, once you toss the coin, you either have a head or a tail". Thus, you have a 95% chance of creating a 95% CI for a parameter that contains the true value. However, once you've done it, your CI either covers the parameter or it doesn't.
Is a 95 percent confidence interval for a mean wider than a 99 percent confidence interval?
No, it is not. A 99% confidence interval would be wider. Best regards, NS
What does a 95 percent confidence interval tell you about the population proportion?
There is a 95% probability that the true population proportion lies within the confidence interval.
Difference between 95 percent and 99 percent confidence interval?
4.04%
What would happen to the width of the confidence interval if the level of confidence is lowered from 95 percent to 90 percent?
decrease
What is the Z value for 95 percent confidence interval estimation?
1.96
When the sample size and sample standard deviation remain the same a 99 percent confidence interval for a population mean will be narrower than the 95 percent confidence interval for the mean?
Never!
When the sample size increase what will happen to the 95 percent confidence interval?
It becomes narrower.
What does it mean to have 95 percent confidence in an interval estimate?
It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.
When determining the 95 percent confidence interval for a population mean with known sigma the value of the critical value of z is equal to?
1.96
When comparing the 95 percent confidence and prediction intervals for a given regression analysis what is the relation between confidence and prediction interval?
Confidence interval considers the entire data series to fix the band width with mean and standard deviation considers the present data where as prediction interval is for independent value and for future values.
Does the population mean have to fall within the confidence interval?
No. For instance, when you calculate a 95% confidence interval for a parameter this should be taken to mean that, if you were to repeat the entire procedure of sampling from the population and calculating the confidence interval many times then the collection of confidence intervals would include the given parameter 95% of the time. And sometimes the confidence intervals would not include the given parameter.
What is 95 percent Confidence level?
OVERCONFIDENT
