An introduction to medical statistics for health care professionals: hypothesis tests and estimation.

This article is the second in a series of three that will give health care professionals (HCPs) a sound introduction to medical statistics (Thomas, 2004) . The objective of research is to find out about the population at large. However, it is generally not possible to study the whole of the populati...

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Publicado en:Musculoskeletal Care Vol. 3; no. 2; pp. 102 - 109
Autor principal: Thomas E
Formato: tables/charts Journal Article
Publicado: Wiley-Blackwell 2005
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Wiley-Blackwell
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        atl: An introduction to medical statistics for health care professionals: hypothesis tests and estimation.
      aug:
        au: Thomas E
        affil: Primary Care Sciences Research Centre, Keele University, North Staffordshire, ST5 5BG; +44 1782 583924; e.thomas@keele.ac.uk
      sug:
        subj:
          Health Personnel Education
          Statistics Education
          Confidence Intervals
          Inferential Statistics
          P-Value
          Sampling Error
          Statistical Significance
      ab: This article is the second in a series of three that will give health care professionals (HCPs) a sound introduction to medical statistics (Thomas, 2004) . The objective of research is to find out about the population at large. However, it is generally not possible to study the whole of the population and research questions are addressed in an appropriate study sample. The next crucial step is then to use the information from the sample of individuals to make statements about the wider population of like individuals. This procedure of drawing conclusions about the population, based on study data, is known as inferential statistics. The findings from the study give us the best estimate of what is true for the relevant population, given the sample is representative of the population. It is important to consider how accurate this best estimate is, based on a single sample, when compared to the unknown population figure. Any difference between the observed sample result and the population characteristic is termed the sampling error. This article will cover the two main forms of statistical inference (hypothesis tests and estimation) along with issues that need to be addressed when considering the implications of the study results.
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    language: English
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