1. A meaningful reason in order to eliminate an outlier from a dataset is the ou

Question

1. A meaningful reason in order to eliminate an outlier from a dataset is the outlier is greater than the standard deviation. (TRUE/FALSE)

2)An outlier in a dataset is an extreme point that may lie in the control limits. (TRUE/FALSE)

3. If a sample size increases, the standard deviation (_x ) of the sample increases. (TRUE/FALSE)

4. Standard deviation is an estimation of the standard error of a population mean. (TRUE/FALSE)

5. A six-sigma process represents that the distance from the process mean to the nearest specification is six standard deviations. (TRUE/FALSE)

6. Specification limits and control limits are relevant to each other, therefore, it is convenient to show specification limits on the control chart. (TRUE/FALSE)

7. A small process capability is often preferred, since it is easier to maintain a process mean at the center of the specifications for long periods of time. (TRUE/FALSE)

8. A point more than three interquartile ranges from the box edge is called an extreme outlier. (TRUE/FALSE)

9. The difference in population proportions can be estimated by using the z formula for different sample proportion of population. (TRUE/FALSE)

Explanation / Answer

3. If a sample size increases, the standard deviation (_x ) of the sample increases.

sd = (x-mean)2 / n-1

as sample size (n) increases denominator of the standard deviation is decreases.

This is false statement.

4. Standard deviation is an estimation of the standard error of a population mean.

The standard error of the mean (SEM) (i.e., of using the sample mean as a method of estimating the population mean) is thestandard deviation of those sample meansover all possible samples (of a given size) drawn from the population

This is true statement.

6. Specification limits and control limits are relevant to each other, therefore, it is convenient to show specification limits on the control chart.

This is also true statement.

8.A point more than three interquartile ranges from the box edge is called an extreme outlier.

if a data point is below Q1 – 1.5×IQR or above Q3 + 1.5×IQR, are called as outliers.

This as an false statement.

9. The difference in population proportions can be estimated by using the z formula for different sample proportion of population.

This is true statement.

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