Answer:
The width or range of the confidence interval with sample size 200 will be about half of that of the confidence interval with sample 50.
Explanation:
Confidence Interval for the population mean is basically an interval of range of values where the true population mean can be found with a certain level of confidence.
Mathematically,
Confidence Interval = (Sample mean) ± (Margin of error)
Margin of Error is the width of the confidence interval about the mean.
It is given mathematically as,
Margin of Error = (Critical value) × (standard Error of the mean)
Confidence Interval = (Sample mean) ± [(Critical value) × (standard Error of the mean)
- For the two random samples, of sizes 50 and 200, the Central limit theorem allows us to say that the sample mean is approximately equal to the population mean as this random sample satisfies the condition of being a simple random sample and a distribution obtained from a normal distribution.
- Making the right assumption that population standard deviation is known and z-distribution is used to find the critical value
Critical value for 95% = 1.96
The critical value for both samples are the same then.
- Standard Error of the mean = σₓ = (σ/√n)
where σ = population standard deviation
n = sample size
For the two distributions
Confidence Interval = (Sample mean) ± [(Critical value) × (Standard Error of the mean)
(Sample mean)₅₀ = (Sample mean)₂₀₀
(Critical value)₅₀ = (Critical value)₂₀₀
(Standard Error of the mean)₅₀ = (σ/√50) = 0.1414σ
(Standard Error of the mean)₂₀₀ = (σ/√200) = 0.0707σ
0.1414σ = 2 × 0.0707σ
(Standard Error of the mean)₅₀ = 2 × (Standard Error of the mean)₂₀₀
(Standard Error of the mean)₅₀ > (Standard Error of the mean)₂₀₀
Hence,
(Margin of Error)₅₀ > (Margin of Error)₂₀₀
(Margin of Error)₅₀ = 2 × (Margin of Error)₂₀₀
Confidence Interval = (Sample mean) ± (Margin of error)
Hence, the width or range of the confidence interval with sample size 50 will be about two times larger than the confidence interval with sample 200.
Hope this Helps!!!