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An additional account, payroll payable, is created for this transaction. The previous entry is posted as follows: Wages Expense (Expense) Debit Credit Balance $3,400 400 $3,400 3,800 Salaries Expense (Expense) Debit Credit Balance $1,800 480 $1,800 2,280 Payroll Payable (Liability) Debit Credit Balance $ 880 $ 880

, Elkin & Leippe, 1986; Losch & Cacioppo, 1990), and such arousal has been shown to be subjectively unpleasant (Elliot & Devine, 1994) When the arousal can be plausibly misattributed to some unrelated environmental agent (rather than to the true dissonancearousing event), dissonance-based attitude change fails to occur (eg, Fazio et al, 1977; Zanna & Cooper, 1974) However, evidence for the mediational role of arousal in eliciting dissonance-based attitude change is equivocal Some work, for example, suggests that the experience of dissonance has less to do with arousal per se and more to do with feeling unpleasant (eg, Higgins, Rhodewalt, & Zanna, 1979; Losch & Cacioppo, 1990) Additionally, in contrast to the predictions of dissonance theory, attitude change following a dissonance induction can sometimes fail to reduce dissonance-based.

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2. Data understanding phase a. Collect the data. b. Use exploratory data analysis to familiarize yourself with the data, and discover initial insights. c. Evaluate the quality of the data. d. If desired, select interesting subsets that may contain actionable patterns. 3. Data preparation phase a. This labor-intensive phase covers all aspects of preparing the nal data set, which will be used for subsequent phases, from the initial, raw, dirty data. b. Select the cases and variables you want to analyze and that are appropriate for your analysis. c. Perform transformations on certain variables, if needed. d. Clean the raw data so that it is ready for the modeling tools. 4. Modeling phase a. Select and apply appropriate modeling techniques. b. Calibrate model settings to optimize results. c. Often, several different techniques may be applied for the same data mining problem.

If you need to have a visitor enter a password, you probably want to include two password fields to enable the visitor to retype the password. You might also want to include a JavaScript to check and make sure the value of both password fields is the same before they can leave the page. This saves you the trouble of doing server processing to confirm the password.

Table 6-5 Host-Specific Backend Setup (versions prior to 0.19)

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vides tentative evidence suggesting that the MBI-GS may also be modified for use among athletes, although the ABQ did perform more adequately in the MTMM analyses on several accounts Based on the psychometric results, construct validity analysis, and practical considerations, the results support the use of the ABQ to assess athlete burnout THE EXTENT AND PREVALENCE OF ATHLETE BURNOUT At this time there are no published epidemiological reports on athlete burnout Concerns about the occurrence and prevalence of burnout have been grounded more in anecdotal evidence and speculation than inferences based on population-based surveys Of course, the previously described conceptual and measurement difficulties have contributed to the lack of clarity on the extent of the problem not that any instance is unproblematic for a suffering athlete.

Another useful approach in the evaluation of an income statement is to find the average check per guest for each sales division, cost per guest by items, and operating income and net income (after tax) figures on an average per-guest basis. Sales revenue / Guests Average sales revenue per guest Cost item / Guests Average cost per guest Operating income / Guests Average operating income per guest Trend results are similar to comparative and common-size statements, except that they show figures for several successive periods, showing the change in dollars and the percentage change from each period to the next: Current period Last period $ Change / Last period Trend %

The athlete burnout data presently available have been obtained largely from nonrepresentative samples of participants thought to be at risk of experiencing elevated levels of burnout As a result, it cannot be argued that these data are representative of the overall population of athletes involved in serious competition, or even a given subpopulation of competitive athletes (eg, rugby players) Nonetheless, these data do make it reasonable to believe that some athletes suffer from a level of burnout that may be nontrivial for performance and well-being We have summarized descriptive statistics from selected studies employing the ABQ in Table 281 Across the studies listed in Table 281, there is some consistency in the mean levels of reported physical and emotional exhaustion, reduced accomplishment, and sport devaluation.

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