Here is the synopsis of our sample research paper on Reliability and Validity in Research. Have the paper e-mailed to you 24/7/365.
Essay / Research Paper Abstract
A 5 page paper discussing the concepts of reliability and validity, their importance to research and the ways in which they can be either negated or enhanced. The paper includes a discussion of general statistical analyses and the need for caution in that arena as well. Bibliography lists 4 sources.
Page Count:
5 pages (~225 words per page)
File: CC6_KSresRelVal2.rtf
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Unformatted sample text from the term paper:
Twain categorized lies for us, defining three types: "lies, damned lies and statistics." Another observer quipped many years later, "Figures dont lie, but liars figure."
There are a raft of poorly-designed studies available, and researchers can "prove" virtually anything they wish by neglecting to address the concepts of validity and reliability
in their designs. Well-designed research can stand as relevant for decades, but lesser efforts may or may not be useful in practice at any time. Definitions of Reliability and
Validity There are three types of questions commonly used in qualitative research projects: descriptive, relational and causal. The most demanding of these
three is the causal questionnaire. Descriptive questions are those that are simply opinion polls. They seek to find out the opinions of a certain population. Relational studies
are those in which questions are used to define relationships between two or more variables. Relational studies are most likely to use statistical examination of data to determine whether
links exist between variables. The Causal study is a cumulative effort of the three types of questions that are asked. Cause and
effect, that is, "causal" questions are those which would compare the type of activity (the cause) with the effect of that cause. This type of relational study, according to
Cornell University, assumes that you can "first describe each of the variables you are trying to relate" and that a causal study assumes that you can describe "both the cause
and the effect variables and that you can show that they are related to each other" (Trochim, 2004). When we consider whether or
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