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Q: What is the Z value for 91 percent confidence interval estimation?

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1.15

ss

1.96

Pr{z<=1.0805}~=0.86

For a two-tailed interval, they are -1.645 to 1.645

The answer depends on whether the test is one-tailed or two-tailed.One-tailed: z = 1.28 Two-tailed: z = 1.64

The two tailed critical value is Â±1.55

The answer will depend on whether the interval is one-sided or two-sided; and if two-sided, whether it is symmetrical.For a symmetrical two-sided confidence interval, the Z value is 0.974114The answer will depend on whether the interval is one-sided or two-sided; and if two-sided, whether it is symmetrical.For a symmetrical two-sided confidence interval, the Z value is 0.974114The answer will depend on whether the interval is one-sided or two-sided; and if two-sided, whether it is symmetrical.For a symmetrical two-sided confidence interval, the Z value is 0.974114The answer will depend on whether the interval is one-sided or two-sided; and if two-sided, whether it is symmetrical.For a symmetrical two-sided confidence interval, the Z value is 0.974114

The answer will depend on whether the interval in one or two sided. One-sided: Z < 1.28 or Z > -1.28 Two-sided: -1.64 < Z < 1.64

No. The width of the confidence interval depends on the confidence level. The width of the confidence interval increases as the degree of confidence demanded from the statistical test increases.

1.96

It depends on whether the interval is one sided or two sided. The critical value for a 2-sided interval is 1.75

2.326 (one sided) or 2.578 (two sided)

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.

The confidence interval consists of a central value and a margin of error around that value. If it is an X% confidence interval then there is a X% probability that the true value of the statistic in question lies inside the interval. Another way of looking at it is that if you took repeated samples and calculated the test statistic each time, you should expect X% of the test statistics to fall within the confidence interval.

99.9 CI means that there is a 99.9% chance the CI limits contains the value you are looking for.

Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.

Statistical estimates cannot be exact: there is a degree of uncertainty associated with any statistical estimate. A confidence interval is a range such that the estimated value belongs to the confidence interval with the stated probability.

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

The answer depends on whether the interval is one-sided or two-sided and, if two-sided, whether or not it is symmetrical.

The value for a one-sided confidence interval of 86% is 1.08

Expected value is the outcome of confidence of how probability distribution is characterized. If the expected value is greater than the confidence interval then the results are significant.

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.

The answer will depend on whether the confidence interval is one-sided, or two-sided and, if two-sided, whether or not it is symmetrical. Symmetrical 2-sided: Â±0.189

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.