Tools for Social Work

Using Standardization and the Normal Curve to Enhance your Social Work Practice, Education & Research

Archive for the ‘Notes’ Category

(c.2008, William T. Beverly, Ph.d.)

Solving Problems with the Standard Normal Curve

Posted by nepeht on December 24, 2008

http://videos.howstuffworks.com/hsw/11359-solving-problems-with-the-standard-normal-curve-video.htm

A video from “How Stuff Works”.

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Normal Curve Tests of Means and Proportions

Posted by nepeht on December 24, 2008

http://faculty.chass.ncsu.edu/garson/PA765/normal.htm

By Professor G. David Garson

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Slideshow About the Basics of Standard Deviation and Variance

Posted by nepeht on December 22, 2008

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Slideshow Demonstrating Use of The Normal Distribution to Analyze Medical Data

Posted by nepeht on December 21, 2008

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Probability Slideshow posted by Mike Shelly on Slideshare.com

Posted by nepeht on December 19, 2008

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Graph and Importance of the Normal Distribution

Posted by nepeht on December 19, 2008

Click here to see graph at Stattucino.com.

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Percentile and Percentile Rank

Posted by nepeht on November 24, 2008

http://en.wikipedia.org/wiki/Percentile.

A percentile is the value of a variable below which a certain percent of observations fall. So the 20th percentile is the value (or score) below which 20 percent of the observations may be found. The term percentile and the related term percentile rank are often used in descriptive statistics as well as in the reporting of scores from norm-referenced tests.

The 25th percentile is also known as the first quartile(Q1); the 50th percentile as the median or second quartile(Q2); the 75th percentile as the third quartile (Q3).

 http://en.wikipedia.org/wiki/Percentile_rank.

The percentile rank of a score is the percentage of scores in its frequency distribution which are lower. For example, a test score which is greater than 85% of the scores of people taking the test is said to be at the 85th percentile. Percentile ranks are commonly used to clarify the interpretation of scores on standardized tests. For the test theory, the percentile rank of a raw score is interpreted as the percentages of examinees in the norm group who scored below the score of interest.[1]

Percentile ranks (PRs or “percentiles”) are normally distributed and bell-shaped while normal curve equivalents (NCEs) are uniform and rectangular in shape. Percentile ranks are not on an equal-interval scale; that is, the difference between any two scores is not the same between any other two scores. For example, 50 – 25 = 25 is not the same distance as 60 – 35 = 25 because of the bell-curve shape of the distribution. Some percentile ranks are closer to some than others. Percentile rank 30 is closer on the bell curve to 40 than it is to 20.

From Wikipedia

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Range

Posted by nepeht on November 22, 2008

http://www.mathgoodies.com/lessons/vol8/range.html.

Describes Range.

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Sample, Population and P Value Discussion

Posted by nepeht on November 22, 2008

http://www.graphpad.com/articles/pvalue.htm.

A discussion of the meanings of P Value, Sample and Population.

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P Value

Posted by nepeht on November 22, 2008

http://en.wikipedia.org/wiki/P-value.

In statistical hypothesis testing, 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. The fact that p-values are based on this assumption is crucial to their correct interpretation.

More technically, a p-value of an experiment is a random variable defined over the sample space of the experiment such that its distribution under the null hypothesis is uniform on the interval [0,1]. Many p-values can be defined for the same experiment.

 From Wikipedia.

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