Page 51 - Quantitative Data Analysis

Quantitative Data Analysis
Simply Explained Using SPSS

Level of Significance

There is an amount of error associated with the confidence. Alpha
(α) is the probability of an incorrect conclusion. Level of confidence
refers to the probability that the researcher is making a correct
conclusion. Level of significance (a.k.a. -level) is a predetermined
level of the probability of rejecting the null when it is actually true.

There is an amount of error associated with the confidence. Alpha is
the probability of an incorrect conclusion. The researcher chooses
how confident he or she wants to be in their test. This also
determines the chance of error the researcher is willing to make.
C=1 - ; C: Confidence level; : Probability of an error

Common values for alpha includes: .05, .01, .001 (5%, 1%, and .01%
respectively).

p Value

The p-value is the probability of obtaining a result at least as
extreme as the one that was actually observed, given that the null
hypothesis is true. p<.001 implies that the probability this difference
or one larger could arise given the null is true is less than 0.1%.

SPSS and other statistical software provide p value of all statistical
tests. When the conclusion is to “reject the null hypothesis” it is
known that p <α. When the conclusion is to “fail to reject the null
hypothesis” it is known that p >α.

The Theory and Applications of Statistical Inferences 35