This paper discusses the field of inferential statistics and its application.
Written in 2005; 2,435 words; 15 sources; APA; $ 74.95
Paper Summary:
This paper explains that psychologists use statistics to make sense of the human behaviors; through observation measurement and statistical inference, researchers are able to take the abstract and make it more understandable. The author points out that, in inferential statistics, researchers use probability to make generalizations about the entire population based on the results from the research sample. The paper relates that statistics can be used to dictate public policy; thereby, it is especially important that mis-measurements do not occur particularly by drawing samples from non-normative or incomplete populations; while seemingly straightforward, statistics require judicious application of ethical behavior. 2 figures. 6 tables.
Table of Contents
History
Descriptive and Inferential Statistics
Samples and Populations
Probability
Data
Measures of Central Tendency
Central Limit Theorem
Hypothesis Testing
Related Samples
Correlation of Pre and Post Test
What Does Is All Mean?
From the Paper:
"Some of the earliest work in statistics was done by Sir William Perry in 1532, when he began to record the number of deaths in London on a weekly basis. Later in the 1600, James Bernoilli, a Swiss mathematician, begin using probability to predict outcomes. In the 1700s, it was Thomas Bayer who gave birth to the concept of inferential statistics. The normal distribution was discovered in 1733 by a Huguenot refugee de Moivre as an approximation to the binomial distribution when the number of trials is too large. Today, not only do scientists but also many professions rely on statistics to understand behavior and ideally make predictions about what circumstances relate to or cause these behaviors."
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