Study guides

Q: Is a 95 percent confidence interval for a mean wider than a 99 percent confidence interval?

Write your answer...

Submit

Related questions

Never!

The confidence interval is not directly related to the mean.

if the confidence interval is 24.4 to 38.0 than the average is the exact middle: 31.2, and the margin of error is 6.8

A confidence interval of x% is an interval such that there is an x% probability that the true population mean lies within the interval.

The Confidence Interval is a particular type of measurement that estimates a population's parameter. Usually, a confidence interval correlates with a percentage. The certain percentage represents how many of the same type of sample will include the true mean. Therefore, we would be a certain percent confident that the interval contains the true mean.

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.

All things being equal, a wider confidence interval (CI) implies a higher confidence. The higher confidence you want, the wider the CI gets. The lower confidence you want, the narrower the CI gets The point estimate will be the same, just the margin of error value changes based on the confidence you want. The formula for the CI is your point estimate +/- E or margin of error. The "E" formula contains a value for the confidence and the higher the confidence, the larger the value hence the wider the spread. In talking about the width of the CI, it is not correct to say more or less precise. You would state something like I am 95% confident that the CI contains the true value of the mean.

1.96

1.0966

The mean plus or minus 2.576 (4/sqr.rt. 36)= 1.72 So take your average plus or minus 1.72 to get your confidence interval

The formula for margin of error is (Z*)*(Standard Deviation))/(sqrt(N)), so as N increases, the margin of error decreases. Here N went from 100 to 5000, so N has increased by 4900. This means the margin of error decreases. Since the confidence interval is the mean plus or minus the margin of error, a smaller margin of error means that the confidence interval is narrower.

It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.

Confidence intervals may be calculated for any statistics, but the most common statistics for which CI's are computed are mean, proportion and standard deviation. I have include a link, which contains a worked out example for the confidence interval of a mean.

What percentage of times will the mean (population proportion) not be found 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.

You probably mean the confidence interval. When you construct a confidence interval it has a percentage coverage that is based on assumptions about the population distribution. If the population distribution is skewed there is reason to believe that (a) the statistics upon which the interval are based (namely the mean and standard deviation) might well be biased, and (b) the confidence interval will not accurately cover the population value as accurately or symmetrically as expected.

12

Confidence intervals may be calculated for any statistics, but the most common statistics for which CI's are computed are mean, proportion and standard deviation. I have include a link, which contains a worked out example for the confidence interval of a mean.

For normally distributed data. One standard deviation (1σ)Percentage within this confidence interval68.2689492% (68.3% )Percentage outside this confidence interval31.7310508% (31.7% )Ratio outside this confidence interval1 / 3.1514871 (1 / 3.15)

Variance, t-value, sample mean

It depends whether or not the observations are independent and on the distribution of the variable that is being measured or the sample size. You cannot simply assume that the observations are independent and that the distribution is Gaussian (Normal).

Mean plus or minus 1.95 SEM. Mean minus 1,95 SEM to Man plus 1,95 SEM.

normal distribution

Typically, the mean is the center and the interval extends a fixed number of standard-errors-of-the mean in wither direction. M+/- 1 SEM for example. I guess because you don't know, I should give you the simplest.

sample size, n = 140standard deviation, s = 11.45standard error of the mean, SE = s / n^1/2 = 11.45 / 140^1.2 = 0.967795% confidence interval => mean +- 1.96SE95% CI = 86.5 - 1.96*0.9677; 86.5 + 1.96*0.9677= 84.6; 88.4