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.
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The margin of error increases as the level of confidence increases because the larger the expected proportion of intervals that will contain the parameter, the larger the margin of error.
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.
It depends on whether it is the Type I Error or the Type II Error that is increased.
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.
1.0966