MAS106elearn Topic 1.pdf - Chapter 1 INTRODUCTION...

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Mathematical Applications for the Management, Life, and Social Sciences
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Chapter 10 / Exercise 58
Mathematical Applications for the Management, Life, and Social Sciences
Harshbarger
Expert Verified
Chapter 1 INTRODUCTION Introduction These notes are intended to provide the student with a conceptual overview of statistical methods with emphasis on applications commonly used in pharma- ceutical and epidemiological research which are the main areas of research in Biostatistics. The goal is to provide the student with the information needed to be able to interpret the types of studies that are reported in academic journals, as well as the ability to perform such analyses. Examples are taken from journals in the pharmaceutical and health sciences fields. Learning Objectives Upon completion of this topic, the student should be able to distinguish between a population and a parameter . define a parameter and a statistic. know the different types of basic study designs. 1.1 Population and Samples A population is the set of all measurements of interest to a researcher. Typically, the population is not observed, but we wish to make statements or inferences concerning it. Populations can be thought of as existing or conceptual . Existing populations are well–defined sets of data containing elements that could be identified explicitly. Examples include: 1
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Mathematical Applications for the Management, Life, and Social Sciences
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Chapter 10 / Exercise 58
Mathematical Applications for the Management, Life, and Social Sciences
Harshbarger
Expert Verified
PO1 CD 4 counts of every American diagnosed with AIDS as of January 1, 1996. PO2 Amount of active drug in all 20 mg Prozac capsules manufactured in June 1996. PO3 Presence or absence of prior myocardial infarction in all American males between 45 and 64 years of age. Conceptual populations are non–existing, yet visualized or imaginable sets of measurements. This could be thought of as characteristics of all people with a disease, now or in the near future, for instance. It could also be thought of as the outcomes if some treatment were given to a large group of subjects. In this last setting, we do not give the treatment to all subjects, but we are interested in the outcomes if it had been given to all of them. Examples include: PO4 Bioavailabilities of a drug’s oral dose (relative to i. v. dose) in all healthy subjects under identical conditions. PO5 Presence or absence of myocardial infarction in all current and future high blood pressure patients who receive short–acting calcium channel blockers. PO6 Positive or negative result of all pregnant women who would ever use a particular brand of home pregnancy test Samples are observed sets of measurements that are subsets of a cor- responding population. Samples are used to describe and make inferences concerning the populations from which they arise. Statistical methods are based on these samples having been taken at random from the population. However, in practice, this is rarely the case. We will always assume that the sample is representative of the population of interest. Examples include: SA1 CD 4 counts of 100 AIDS patients on January 1, 1996.

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