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It depends whether or not the observations are independent and on the distribution of the variable that is being measured or the sample size. You cannot simply assume that the observations are independent and that the distribution is Gaussian (Normal).
Confidence IntervalsConfidence interval (CI) is a parameter with a degree of confidence. Thus, 95 % CI means parameter with 95 % of confidence level. The most commonly used is 95 % confidence interval.Confidence intervals for means and proportions are calculated as follows:point estimate ± margin of error.
A bank wishing to estimate the mean balances owed by their MasterCard customers within 75 miles with a 98 percent confidence can use the following formula to calculate the required sample size: Sample size = (Z-score)2 * population standard deviation / (margin of error)2 Where Z-score = 2.326 for 98 percent confidence Population standard deviation = 300 Margin of error = desired confidence intervalSubstituting the values into the formula the required sample size is: 2.3262 * 300 / (Confidence Interval)2 = 553.7Therefore the bank would need to have a sample size of 554 to estimate the mean balances owed by their MasterCard customers within 75 miles with a 98 percent confidence.
25 percent
Never!
The data in the table below represent time study observations for a woodworking operation.Based on the observations, determine the standard time for the operation, assuming an allowance of 15 percent of job time.How many observation s would be needed to estimate the mean time for element 2 within 1 percent if it's true value with a 95.5 percent confidence?How many observations would be needed to estimate the mean time for element 2 within 0.01 minute of its true value with a 95.5 percent confidence?ElementPerformanceRatingObservations (Minutes per Cycle)1234561110%1.201.171.161.221.241.152115%0.830.870.780.820.851.323105%0.580.530.520.590.600.54
It depends whether or not the observations are independent and on the distribution of the variable that is being measured or the sample size. You cannot simply assume that the observations are independent and that the distribution is Gaussian (Normal).
About 80% are metals.
What number of observations would be required in a time study in order to obtain a 95 percent confidence that the average time observed was no more than 0.6 minutes from the true mean, assuming a standard deviation of cycle time of 1.8 minutes?
Confidence IntervalsConfidence interval (CI) is a parameter with a degree of confidence. Thus, 95 % CI means parameter with 95 % of confidence level. The most commonly used is 95 % confidence interval.Confidence intervals for means and proportions are calculated as follows:point estimate ± margin of error.
decrease
A bank wishing to estimate the mean balances owed by their MasterCard customers within 75 miles with a 98 percent confidence can use the following formula to calculate the required sample size: Sample size = (Z-score)2 * population standard deviation / (margin of error)2 Where Z-score = 2.326 for 98 percent confidence Population standard deviation = 300 Margin of error = desired confidence intervalSubstituting the values into the formula the required sample size is: 2.3262 * 300 / (Confidence Interval)2 = 553.7Therefore the bank would need to have a sample size of 554 to estimate the mean balances owed by their MasterCard customers within 75 miles with a 98 percent confidence.
25 percent
No, it is not. A 99% confidence interval would be wider. Best regards, NS
It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.
0.040
OVERCONFIDENT