Which of the following statistics are unbiased estimators of population​ paramet

Zoe Oneal

Zoe Oneal

Answered question

2021-10-26

Which of the following statistics are unbiased estimators of population​ parameters?
Choose the correct answer below. Select all that apply.
A) Choose the correct answer below. Select all that apply.
B) Sample variance used to estimate a population variance.
C) Sample proportion used to estimate a population proportion.
D) Sample mean used to estimate a population mean.
E) Sample range used to estimate a population range.
F) Sample standard deviation used to estimate a population standard deviation

Answer & Explanation

faldduE

faldduE

Skilled2021-10-27Added 109 answers

Step 1 
Idea and motivation
A rule that instructs you on how to compute an estimate based on a sample is known as an estimator.
The set of all potential values is referred to as the parameter space.
Unbiasedness: An estimator Tn=T(x1, x2,,xn) is said to be an unbiased estimator of γ(θ) if E(Tn)=γ(θ) for all θΘ 
Baisedness: An estimator Tn=T(x1, x2,,xn) is said to be an unbiased estimator of γ(θ) if E(Tn)γ(θ) for all θΘ 
Fundamentals 
The sample mean formula is,
x=xn 
The sample variance equation is,
s2=1ni=1n(xix)2 
S2=1n1i=1n(xix)2 
The formula for standard deviation is, 
s=s2 
Step 2 
The median, ranges, and standard deviation are biased estimators based on the sample's known information.
Unbiased estimates of the parameters of the population are provided by the sample mean, variance, and proportion.
Step 2 
From the known information E(x)=μ, E(p^)=p and E(s2)=σ2. Therefore, sample mean, variance, and proportion are the unbiased estimators.
To calculate population variance, one uses sample variance.
used to calculate the sample proportion of the population.
To calculate the population mean, utilize the sample mean.
An objective estimate of population variance is the sample variance. Both the sample proportion and the sample mean are unbiased estimates of the population's proportion and mean, respectively.

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