The city wishes to estimate the average commute distance for all city employees. They collect a random sample of 97 employees and find a sample mean of ¯x=7.1x¯=7.1 miles. They also assume a population standard deviation of σ=1.5σ=1.5 miles. Calculate the z interval to estimate, μμ, the average commute distance for all city employees with 95% confidence. Round your answers to 2 decimal places. Find the Critical Value z*: Point Estimate: Margin of Error: Write the interval as (lower bound, upper bound)
The city wishes to estimate the average commute distance for all city employees. They collect a random sample of 97 employees and find a sample mean of ¯x=7.1x¯=7.1 miles. They also assume a population standard deviation of σ=1.5σ=1.5 miles. Calculate the z interval to estimate, μμ, the average commute distance for all city employees with 95% confidence. Round your answers to 2 decimal places. Find the Critical Value z*: Point Estimate: Margin of Error: Write the interval as (lower bound, upper bound)
The city wishes to estimate the average commute distance for all city employees. They collect a random sample of 97 employees and find a sample mean of ¯x=7.1x¯=7.1 miles. They also assume a population standard deviation of σ=1.5σ=1.5 miles. Calculate the z interval to estimate, μμ, the average commute distance for all city employees with 95% confidence. Round your answers to 2 decimal places. Find the Critical Value z*: Point Estimate: Margin of Error: Write the interval as (lower bound, upper bound)
The city wishes to estimate the average commute distance for all city employees. They collect a random sample of 97 employees and find a sample mean of ¯x=7.1x¯=7.1 miles. They also assume a population standard deviation of σ=1.5σ=1.5 miles. Calculate the z interval to estimate, μμ, the average commute distance for all city employees with 95% confidence.
Round your answers to 2 decimal places.
Find the Critical Value z*:
Point Estimate: Margin of Error:
Write the interval as (lower bound, upper bound)
Definition Definition Method in statistics by which an observation’s uncertainty can be quantified. The main use of interval estimating is for describing a range that is made by transforming a point estimate by determining the range of values, or interval within which the population parameter is likely to fall. This range helps in measuring its precision.
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