The manager of a warehouse would like to know how many errors are made when a product's serial number is read by a bar-code reader. Six samples are collected of the number of scanning errors: 36, 14, 21, 39, 11, and 2 errors, per 1,000 scans each. Just to be sure, the manager has six more samples taken:

33, 45, 34, 17, 1, and 29 errors, per 1,000 scans each

How reasonable is it to expect that the small sample represents larger samples?

1A. 20.5

2A. 14.54

1B. 14.625

2B. quite good reasonable

Step-by-step explanation:

Mean is used to measure central tendency (i.e. representative of data) and standard deviation is use to measure dispersion of data. The formula use to calculate mean and variance is :

1A. Mean of six sample =

⇒  

⇒ Mean = 20.5

Standard deviation of six sample =

⇒ σ = 14.54

2A. Total number of error = 36 + 14 + 21 + 39 + 11 + 2 = 123

Total number of error made by all scans is 123 error per 6000 scans.

1B. Mean of all 12 samples is:

⇒  

⇒ Mean = 23.5

Standard deviation of all 12 samples =

⇒ σ = 14.625

2B. Taking small sample instead of large sample can be quite risky sometimes as larger sample give us more accurate result than small sample.

But here we can take a small sample because the mean of both the size of the sample is near about.

Step-by-step explanation: