1. Population is the entire group of objects about which information is wanted.

2. A sample is a part or subset of the population used to gain information about the whole.

3. A sampling frame is the list of units from which the sample is chosen.

4. Convenience sampling refers to selections of whichever units of the population, not necessarily random, that are easily accessible; samples obtained in this way are often not representative of the population and can lead to misleading conclusions about the population.

5. Biased is the term for when a sampling method produces results that consistently and repeatedly differ from the truth about the population in the same direction.

6. Simple random sample (SRS) of size n refers to a sample of n units chosen in such a way that every collection of n units from the sampling frame has the same chance of being chosen. It is fair or unbiased.

7. Table of random digits is a list of the ten digits like 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9 having the following properties:

a. The digit in any position in the list has the same chance of being any one of 0, 1, 2, 3, 4, 5, 6, 7, 8, or 9.
and b. The digits in different positions are independent in the sense that the value of one has no influence on the value of any other.

8. A parameter is a numerical characteristic of the population. It is a fixed number, but we usually do not know its value.

9. A statistic is a numerical characteristic of the sample. The value of a statistic is known when we have taken a sample, but it changes from sample to sample. Put simply, parameter is to population as statistic is to sample. Example: If out of 1,220 people, 1098 of this sample size responded "yes" to a question, then p equals 1,098 of 1,220 equals 0.90. It is reasonable to use this proportion p equals 0.90 as an estimate of the unknown population proportion p. But if a second sample size of 1,220 were taken, it is almost certain that there would not be exactly 1,098 positive responses. So the value of p will vary from sample to sample. This is called sampling variability.

10. A probability sample is a sample chosen in such a way that every unit in the sampling frame has a known non-zero chance (or probability) of being chosen.