# Confidence interval refers to an approach in statistics

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Confident interval is an approach in statistics that offers some predetermined assurance that measurements of a population can be obtained. Its description is mainly based on limit errors. Some of the intervals that have been used include 99%, 95% and 90%. The 95 percent trust is primarily used for several purposes of these three.
In most cases, almost all research focused on science investigates the area in question more closely and explicitly states the goal of the research. The successful organization is typically used to decide how the data on the research in question are obtained, evaluated and presented. In a lot of instances that research has been conducted, it is always difficult to use all components of a population, therefore, sampling is required in which part of the population is picked to represent the entire population (Šimundić).

This leaves the researcher with a decision to make on what types of intervals to use, the best results being obtained when the intervals are much narrower, and hence the common use of the 95% confidence interval. This is attributed to its statistical significance level being highly acceptable, the level being P < 0.05. Conclusion The standard error, P, is the most common way of determining the confidence interval value, being a measure of the probability that an incident will occur. This is because the confidence interval and the P-value can be used interchangeably. An example of a case in which the 95% confidence interval is implemented, is whereby we are choosing on one sample of a hundred individuals, to be used in research (Šimundić). The 95% confidence interval will result in a 95% of the population having an actual arithmetic mean. This refers to a sample that is so narrow. Work Cited Šimundić, Ana-Maria. Confidence interval. 2008. 19 November 2017. .

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