Examples of using Confidence interval in English and their translations into Thai
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Colloquial
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Ecclesiastic
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Ecclesiastic
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Computer
Read why confidence intervals are important.
For every metric we calculate statistical confidence intervals indicated on our graphs.
Numeric values represent confidence intervals.
The brackets represent confidence intervals.
In our bar graphs we represent confidence intervals as boundaries on either sides of graph bars. In our supporting-metric charts we show confidence intervals as+/- numerical values.
In our bar graphs we represent confidence intervals as boundaries on either sides of graph bars.
Participants in the Info group voted at the same rate as those in the control group, but people in the Info+ Social group voted at a slightly higher rate. Bars represent estimated 95% confidence intervals. Results in the graph are for the approximately six million participants who were matched to voting records. Adapted from Bond et al.(2012), figure 1.
For every metric we have calculated statistical confidence intervals and plotted them on all of the graphs. When confidence intervals overlap for a certain metric, our measured results are too close to declare a winner in a particular category. In those cases, we show a statistical draw. For this reason, some metrics have multiple operator winners.
Participants in the info group voted at the same rate as people in the control condition, but people in the info+ social group voted at a slightly higher rate. Bars represent estimated 95% confidence intervals. Results in the graph include about 6 million participants for whom researchers could match to voting records.
So what's our confidence interval?
Or an interval of-- we have a confidence interval.
So what would be our confidence interval?
Or what is a confidence interval of the difference of means?
What we now need to do is actually tackle the confidence interval.
And now linguistically it sounds a little bit more like a confidence interval.
This isn't just a 95% confidence interval for this parameter right here.
So there's the 95% confidence interval for the mean of this distribution.
And the margin of error is just another way of describing this confidence interval.
And the high end of our confidence interval, 2.34 plus 0.96 is equal to 3.3.
And we have a 95% confidence interval that that difference is between 0.7 and 3.12 pounds.