|
State gives schools extra leeway; Change allows more to meet federal mandates
|
Despite increasingly tough standards, the number of Wisconsin
schools that will be flagged this year for failing to meet federally
mandated reading and math goals will be less than half what it was
last year 51 as opposed to 108 but not because things are getting
better.
Rather, it is the state's controversial calculation method that
allows schools to miss the goals by substantial percentages without
having it count against them.
For the same reason, only one school district in...
Related newspaper, magazine, and journal articles from HighBeam Research
|
Graphing within-subjects confidence intervals using SPSS and S-Plus
Behavior Research Methods
; Within-subjects confidence intervals are often appropriate to report and to display. Loftus and Masson (1994) have reported methods to calculate these, and their use is becoming common. In the present article, procedures for calculating within-subjects confidence intervals in SPSS and S-Plus are
|
|
Confidence Intervals Within Hypnosis Research
Sleep and Hypnosis
; Confidence intervals within hypnosis would improve research, especially confidence intervals for effect sizes. Moreover, within hypnosis research, confidence intervals are needed for reliability and validity measures. This paper describes definitions and issues related to confidence intervals.
|
|
Most states adjusting school test scores to meet federal standards.
Knight Ridder/Tribune News Service
; Byline: Lisa Deffendall and John Stamper LEXINGTON, Ky. _ All but 19 states are adjusting test scores this year to give some schools a better chance of meeting formidable federal student achievement standards. Schools will be judged on the basis of how small groups of students perform on reading
|
|
Using confidence intervals for graphically based data interpretation*
Canadian Journal of Experimental Psychology
; Abstract As a potential alternative to standard null hypothesis significance testing, we describe methods for graphical presentation of data - particularly condition means and their corresponding confidence intervals - for a wide range of factorial designs used in experimental psychology. We
|
|
The effect of dependence on confidence intervals for a population proportion.
The American Statistician
; 1. INTRODUCTION Let [X.sub.1], [X.sub.2 [X.sub.n] be binomial random variables with common unknown success probability p. Let [n.sub.i] be the number of trials for each [X.sub.i] and N = [n.sub.1] + [n.sub.2] + + [n.sub.n]. When the [X.sub.i]'s are independent, [S.sub.N] = [X.sub.1] + [X.sub.2] +
|
