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Q: What happens to the confidence interval if you increase the confidence level?

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The width of the confidence interval willdecrease if you decrease the confidence level,increase if you decrease the sample sizeincrease if you decrease the margin of error.

The width reduces.

it increases

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.

Confidence intervals represent an interval that is likely, at some confidence level, to contain the true population parameter of interest. Confidence interval is always qualified by a particular confidence level, expressed as a percentage. The end points of the confidence interval can also be referred to as confidence limits.

Confidence level 99%, and alpha = 1%.

confidence level

True.

, the desired probabilistic level at which the obtained interval will contain the population parameter.

it would be with a level of significance of 0.15.

decrease

The answer depends on whether the confidence interval is one sided or two sided.

Confidence IntervalsConfidence 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.

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

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

The smaller the confidence interval, the more certain you are of the answers. Remember confidence level and confidence interval (margin of error) are 2 separate things. So if you are using an industry standard confidence level of 95% and 5% margin of error in a standard statistical table, then you could say, for example, with 95% certainty that 60% of those polled would vote for John McCain. Another way of saying this is even though you did not poll everyone (if you did, it would then become a very expensive census), you can say with a high degree of certainty (95% certainty) that 55% to 65% of those polled will vote for Johnny (sadly).

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

The margin of error is dependent on the confidence interval.I'll give you examples to understand it better.We know:Confidence Interval (CI) = x(bar) ± margin of error (MOE)MOE = (z confidence)(sigma sub x bar, aka standard error of mean)When CI = 95%, MOE = (1.96)(sigma sub x bar)When CI = 90%, MOE = (1.64)(sigma sub x bar)Naturally, the margin of error will decrease as confidence level decreases.

You die.

95% confidence level is most popular

decreases

Increase

I have always been careless about the use of the terms "significance level" and "confidence level", in the sense of whether I say I am using a 5% significance level or a 5% confidence level in a statistical test. I would use either one in conversation to mean that if the test were repeated 100 times, my best estimate would be that the test would wrongly reject the null hypothesis 5 times even if the null hypothesis were true. (On the other hand, a 95% confidence interval would be one which we'd expect to contain the true level with probability .95.) I see, though, that web definitions always would have me say that I reject the null at the 5% significance level or with a 95% confidence level. Dismayed, I tried looking up economics articles to see if my usage was entirely idiosyncratic. I found that I was half wrong. Searching over the American Economic Review for 1980-2003 for "5-percent confidence level" and similar terms, I found: 2 cases of 95-percent significance level 27 cases of 5% significance level 4 cases of 10% confidence level 6 cases of 90% confidence level Thus, the web definition is what economists use about 97% of the time for significance level, and about 60% of the time for confidence level. Moreover, most economists use "significance level" for tests, not "confidence level".

z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.

No. The interval level is more refined and so enables calculations which are not available at the nominal level.

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