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Elementary Statistics

Elementary Statistics. Chapter 2. Census. A census is a sample consisting of the entire population. Definitions. The population is the entire group of objects or individuals under study, about which information is wanted.

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Elementary Statistics

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  1. Elementary Statistics Chapter 2

  2. Census • A census is a sample consisting of the entire population

  3. Definitions • The population is the entire group of objects or individuals under study, about which information is wanted. A unit is an individual object or person in the population. The units are often called subjects if the population consists of people.

  4. Definitions • A sample is a part of the population that is actually used to get information. A variable is a characteristic of interest to be measured for each unit in the sample. The size of the population is denoted by the capital letter N. The size of the sample is denoted by the capital letter n.

  5. Definitions • A parameter is a numerical value that would be calculated using all of the values of the units in the population. A statistic is a numerical value that is calculated using all of the values of the units in the sample.

  6. Bias • A sampling method is biased if it produces results that systematically differ (in one direction) from the truth about the population. A convenience sample is a sample consisting of units of the population that are easily accessible.

  7. Bias • A volunteer sample is a sample consisting of units of the population that chose to respond.

  8. Selection Bias • Selection bias is the systematic tendency on the part of the sampling procedure to exclude or include a certain type of unit.

  9. Selection Bias • Nonresponse bias is the distortion that can arise because a large number of units selected for the sample do not respond or refuse to respond, and these nonresponders have a tendency to be different from the responders.

  10. Selection Bias • Response bias is the distortion that can arise because the wording of a question and the behavior of the interviewer can affect the responses received.

  11. Probability Sampling • A sampling method that gives each unit in the population a known nonzero chance of being selected is called a probability sampling method.

  12. Simple Random Sample • A simple random sampleof size n is a sample of n units selected in such a way that every possible sample of the given size n has the same chance of being selected as any other sample of size n. Samples of different sizes may have different chances of being selected.

  13. Stratified Random Sample • A stratified random sample is selected by dividing or stratifying the population into mutually exclusive subgroups (strata) and taking a simple random sample of units from each stratum. The units sampled from each stratum are combined to form the complete sample.

  14. Systematic Sampling • For a 1-in-k systematic sample, you order the units of the population in some way and randomly select one of the first k units in the ordered list. This selected unit is the first unit to be included in the sample. You continue through the list selecting every kth unit from then on.

  15. Cluster Sampling • In cluster sampling, the units of the population are grouped into clusters. One or more clusters are selected at random. If a cluster is selected, all of the units that form that cluster are included in the sample.

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