lack of confidence in statistical method and technique is termed as
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Answer:
In statistics, a confidence interval (CI) is a type of estimate computed from the statistics of the observed data. This proposes a range of plausible values for an unknown parameter (for example, the mean). The interval has an associated confidence level that the true parameter is in the proposed range. Given observations {\displaystyle x_{1},\ldots ,x_{n}}x_{1},\ldots ,x_{n} and a confidence level {\displaystyle \gamma }\gamma , a valid confidence interval has a probability {\displaystyle \gamma }\gamma of containing the true underlying parameter. The level of confidence can be chosen by the investigator. In general terms, a confidence interval for an unknown parameter is based on sampling the distribution of a corresponding estimator.[1]
Answer:
I suggest reading some books on statistics. It is a quite fundamental question. I will anyway give short answers to your questions, though...
What do you mean by confidence interval in statistical analysis?
It is an interval estimate for a parameter value. It is construced in a way so that, in the long run, a given proportion of these intervals will include the unknown true parameter value. The proportion is given by the "level of confidence". For instance, you can expect that at least 90% of (a large series of) 90% confidence intervals will include the unknown true values of the parameters.
Explanation:
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