A population has a mean of 53 and a standard deviation of 21. A sample of 49 observations will be taken. The probability that the sample mean will be greater than 57.95 is 0.0495.

A subset of a population selected to represent the population is a parameter.

Width of confidence interval is a result of population standard deviation, sample size and confidence level.

If we repeatedly construct 100 intervals of 25 computers from the whole population, 95% of those will not include a true population mean.

One of the steps in hypothesis testing is to compute lower and upper critical values.

A wider interval provides little information.

The larger the sample, the more closely the sampling distribution of the mean will resemble a normal distribution.

One of the conditions of sampling from an infinite population is that each element that must be selected has to be dependent on other elements.

Showing a relationship between a sample statistic and its corresponding population proportion is sampling distribution.

Converting data into information is called statistical inference.