In practice, only one sample is usually taken (in some cases such as "survey data analysis" a small "pilot sample" is used to test the data-gathering mechanisms and to get preliminary information for planning the main sampling scheme). Thus, an important consideration for those planning and interpreting sampling results, is the degree to which sample estimates, such as the sample mean, will agree with the corresponding population characteristic. Because a sample examines only part of a population, the sample mean will not exactly equal the corresponding mean of the population. We must study the behavior of the mean of sample values from different specified populations. Additionally, a sample can, in some cases, provide as much information as a corresponding study that would attempt to investigate an entire population-careful collection of dataįrom a sample will often provide better information than a less careful study that tries to look at everything. The main idea of statistical inference is to take a random sample from a population and then to use the information from the sample to make inferences about particular population characteristics such as the mean (measure of central tendency), the standard deviation (measure of spread) or the proportion of units in the population that have a certain characteristic. Time Series Analysis and Business Forecasting.Danger of Wrong Survey Design and the Interpretation of the Results.Value Measurements Survey Instruments (Rokeach's Value Survey).Questionnaire Design and Surveys Management." parameter" or " sampling" If the first appearance of the word/phrase is not what you are looking for, try F ind Next. Enter a word or phrase in the dialogue box, e.g. To search the site, try Edit | Find in page.
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