Respuesta :
Answer:
Standard deviation.
Step-by-step explanation:
The standard deviation measures how accurate the point estimate is likely to be in estimating a parameter.
The confidence interval measures how accurate the point estimate is likely to be in estimating a parameter.
A confidence interval communicates how accurate our estimate is likely to be.
The confidence interval is a range of of all plausible values of the random variable under test at a given confidence level which is expressed in percentage such as 98%, 95% and 90% of confidence level.
The standard deviation is the parameter to signify the dispersion of data around the mean value of the data.
Researchers prefer it because on the basis of the percentage of certainty in the test result of null hypothesis are accepted or rejected as it includes some chance for errors too. (example 95% sure means 5% not sure) also this gives a range of values and hence good chance to normalize errors.
An interval estimate is typically preferred over a point estimate because
i) it gives us a sense of accuracy of the point estimate
ii) we know the probability that it contains the parameter (e.g., 95%)
iii) it provides us with more possible parameter values
I only
II only
both I and II
all of these
III only
All three statements above are true hence all of these is the answer.
For more information please refer to the link below
https://brainly.com/question/24131141