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To gain more insight into the later years of elite athletes training, Orlick and colleagues (McCaffrey & Orlick, 1989; Orlick & Partington, 1988) interviewed international-level athletes to assess their actual practice behaviors and perceptions of their training The athletes consistently mentioned the need to focus on specific training goals and repeatedly emphasized the importance of concentration and intensity in practice This activity, labeled quality practice by Orlick and Partington, shares many characteristics with deliberate practice, which was subsequently proposed by Ericsson et al (1993) In a follow-up study, McCaffrey and Orlick reported that expert golfers (ie, professional tour golfers ) current practice activities included elements of quality practice and were qualitatively different from the activities of other professional, but less skilled golfers (ie, golf professionals at golf clubs)..

is of rather bad quality Audio can be compressed using many methods and in varying le formats, including MPEG-4 AAC [2], MP3 (MPEG layer III), ASF (advanced streaming format), and Real Audio G2 Audio codecs can compress any complex sound such as music, bird song, waterfall, and high-quality speech (much more natural than typical speech codecs) The audio codecs exploit the redundancies and irrelevancies in the frequency domain using a model of the human auditory system For instance, it won t try to reproduce sounds that the human ear can t perceive But, even compressed using those compression schemes, audio can require several hundreds of kbps to achieve CD quality Speech is used extensively in mobile Internet because of its bandwidth ef ciency Applications of speech clips include voicemails and recording personal moments (audiovisual) But audio applications on mobile phones are growing (eg, MP3 music playback).

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Smoking: cost-effectiveness and, 264 health across life span, 244 health behavior, 246, 247, 248, 249 LCA and, 669, 674, 682 psychosocial risk and, 254 relapses in, 249 250 survival analysis and, 556 557, 560, 561, 562, 563, 564, 569, 575 theory testing and, 261 time series analysis and, 583, 588 590, 601 Snedecor, George, 4 Social desirability, 366, 387, 397 measuring personality and, 383, 384 Social Readjustment Rating Scale, 390 Socioeconomic status (SES): health psychology and, 254 program evaluation and, 337, 339 Software. See Computer software Solomon Four-Group design, 624 Southern Methodist University (SMU), 355, 367, 370 Space: subject, 58 variable space, 58 vector, 58 Spatial Learning Ability Test (SLAT): CTT and, 430, 432 IRT and, 436, 437 438, 441, 443 Spearman-Brown prophecy formula, 432 Spearman s rho. See Ordinal analysis, Spearman s rho Sphericity, 125 127 Spline model, 465 S-PLUS, 58 EDA and, 57 growth curve analysis and, 453 SPSS, 94, 109 animal learning and, 284 CTT and, 431 EDA and, 57 GLM, 126 ordinal analysis and, 659 preparatory data analysis and, 125, 131, 138 normality, 118 sample code, 111 113 SEM analysis and, 92 time series analysis and, 601 Squared multiple correlation (SMC), 134, 148, 149 Stage-sequential ordinal (SSO) model, 679 Stakeholder input, 340 Standardized root mean square residuals (SRMS), 615 Standards for Educational and Psychological Tests, 433, 549 Standard structural equation modeling (SEM) software, 88 Stanford-Binet Intelligence Scale: collinearity and, 133 growth curve analysis and, 449, 454, 473 Statistical Analysis System (SAS), 94, 95, 107 108, 109, 178 animal learning and, 284 CTT and, 431 EDA and, 57 GLM, 126 growth curve analysis and, 453, 458, 475

Suppose that we know a random variable Y and we wish to guess the value of a correlated random variable X. Fano s inequality relates the probability of error in guessing the random variable X to its conditional entropy H (X|Y ). It will be crucial in proving the converse to Shannon s channel capacity theorem in 7. From Problem 2.5 we know that the conditional entropy of a random variable X given another random variable Y is zero if and only if X is a function of Y . Hence we can estimate X from Y with zero probability of error if and only if H (X|Y ) = 0. Extending this argument, we expect to be able to estimate X with a low probability of error only if the conditional entropy H (X|Y ) is small. Fano s inequality quanti es this idea. Suppose that we wish to estimate a random variable X with a distribution p(x). We observe a random variable Y that is related to X by the conditional distribution p(y|x). From Y , we

P11.3 You have the following information about a restaurant: Budgeted Cash Revenue August September October November December $30,300 29,500 27,900 25,100 32,400 Budgeted Credit Revenue $16,000 14,000 13,000 12,000 15,800

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