Here is the synopsis of our sample research paper on Setting Alpha Level. Have the paper e-mailed to you 24/7/365.
Essay / Research Paper Abstract
A 6 page paper discussing the origins and use of alpha in statistical analysis. Alpha is defined as the probability of incurring a Type I error, which is that of rejecting H0 when it is true. It is also found used virtually interchangeably with p-level, which is statistical significance and the exact probability of a Type I error. Bibliography lists 7 sources.
Page Count:
6 pages (~225 words per page)
File: CC6_KSstatsAlpha.rtf
Buy This Term Paper »
Unformatted sample text from the term paper:
as the probability of incurring a Type I error, which is that of rejecting H0 when it is true. It is also found used virtually interchangeably with p-level, which
is statistical significance and the probability "that a particular result would occur by chance if H0 is true. The exact probability of a Type I error" (Glossary M-P, n.d.).
In most research, the alpha level is set at .05 or .01. Research Basics When we consider whether or not test results are
consistent and repeatable, we are talking about the reliability of the test (Patten, 1997). But when we are concerned whether the test is testing what it is supposed to
test, then we are questioning its validity. It is important to note that "these results can be reliable without being valid, but cannot be valid without being reliable" (Kachigan,
1986; p. 218). Therefore, a threat to the validity of any study would be if the measurement system used was not reliable.
Since a measurement system can not be valid if it is not reliable, the amount of validity is limited, therefore, by the degree of reliability (Kachigan, 1986).
The statistical conclusion validity of a study measures the exact amount of validity shown by the test in a given situation. A test can be
considered to be valid in any given situation only to the extent that it is given the same results as the criteria. Adequate sample size can help prevent the
loss of internal validity (Ravid, 1994). A larger population provides results vastly more accurate in obtaining the statistical information needed to come up with a valid result. Importance in
...