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Statistics MArio F Triola Eleventh edition for your course. Maybe the next chapter will be uploaded soon, thank you
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and the Triola Statistics Series by Mario F. Triola
1-1 Review and Preview 1-2 Statistical Thinking 1-3 Types of Data 1-4 Critical Thinking 1-5 Collecting Sample Data
Polls, studies, surveys and other data collecting tools collect data from a small part of a larger group so that we can learn something about the larger group. This is a common and important goal of statistics: Learn about a large group by examining data from some of its members.
In this context, the terms sample and population have special meaning. Formal definitions for these and other basic terms will be given here. In this section we will look at some of the ways to describe data.
is the science of planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data
the complete collection of all individuals (scores, people, measurements, and so on) to be studied; the collection is complete in the sense that it includes all of the individuals to be studied
(^) Sample data must be collected in an appropriate way, such as through a process of random selection. (^) If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistical torturing can salvage them.
(^) Context of the data (^) Source of the data (^) Sampling method (^) Conclusions (^) Practical implications
(^) What do the values represent? (^) Where did the data come from? (^) Why were they collected? (^) An understanding of the context will directly affect the statistical procedure used.
(^) Does the method chosen greatly influence the validity of the conclusion? (^) Voluntary response (or self-selected) samples often have bias (those with special interest are more likely to participate). These samples’ results are not necessarily valid. (^) Other methods are more likely to produce good results.
(^) Make statements that are clear to those without an understanding of statistics and its terminology. (^) Avoid making statements not justified by the statistical analysis.
(^) Consider the likelihood of getting the results by chance. (^) If results could easily occur by chance, then they are not statistically significant. (^) If the likelihood of getting the results is so small, then the results are statistically significant.