To explore how we can change our lives for the better, she draws on the latest research in psychology, sociology, philosophy and neuroscience, as well as insights from figures in literature and history such as George Eliot, Viktor Frankl, Aristotle and the Buddha. She shows us how cultivating connections to others, identifying and working toward a purpose, telling stories about our place in the world, and seeking out mystery, can immeasurably deepen our lives.
To do this she visits remarkable people and places, such as a tight-knit fishing village in the Chesapeake Bay, a dinner where young people gather to share their experiences of profound loss, and a drug kingpin who finds his purpose in helping people get fit. She explores how we might begin to build a culture that leaves space for introspection and awe, cultivates a sense of community, and imbues our lives with meaning. Author : Viktor E. Frankl in deutschen Konzentrationslagern verbringen.
Sie sollen Kraft zum Leben geben. Die Tochter einer Londoner Gangsterfamilie. Eine US-amerikanische Politikerin. Author : Richard J. Author : Martin E. Author : V. We all have a longing to be significant, to make a contribution, to be a part of something noble and purposeful. But know this: You don't have to be a certain age, have a lot of money, or be powerful or famous.
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You can withdraw your e-mail address from the mailing list at any time. Faul, F. Behavior Research Methods , 39 , Download PDF. Behavior Research Methods , 41 , Fixed a bug in z tests: Generic z test: Analysis: Criterion: Compute alpha : The critical z was calculated incorrectly. Fixed a bug in t tests: Linear bivariate regression: One group, size of slope.
Fixed a bug that could occur under very specific circumstances when transferring an effect size from the effect size drawer to the main window. Changed the behaviour of all tests based on the binomial distribution. This change may lead to alpha values larger than the requested alpha values, but now we have the advantage that the upper and lower limits correspond to actual decision boundaries.
Note, however, that the change affects the results only when N is very small. Improvements in the logistic regression module: 1 improved numerical stability in particular for lognormal distributed covariates ; 2 additional validity checks for input parameters this applies also to the poisson regression module ; 3 in sensitivity analyses the handling of cases in which the power does not increase monotonically with effect size is improved: an additional Actual power output field has been added; a deviation of this actual power value from the one requested on the input side indicates such cases; it is recommended that you check how the power depends on the effect size in the plot window.
Fixed a problem in the exact test of Proportions: Inequality, two independent groups uncontional. Fixed a problem in the sensitivity analysis of the logistic regression. The drawers now appear correctly after clicking on the Determine button. Fixed a problem in the test of equality of two variances. The problem did not occur when both sample sizes were identical.
Added an options dialog to the repeated-measures ANOVA which allows a more flexible specification of effect sizes. Fixed a problem in calculating the sample size for Fisher's exact test. The problem did not occur with post hoc analyses. Changing the number of covariates now correctly leads to the appropriate change in the denominator degrees of freedom. Renamed the Repetitions parameter in repeated measures procedures to Number of measurements Repetitions was misleading because it incorrectly suggested that the first measurement would not be counted.
Fixed a problem in the sensitivity analysis of the logistic regression procedure: There was an error if Odds ratio was chosen as the effect size. The problem did not occur when the effect size was specified in terms of Two probabilities. This option has been available for some time in the Windows version see View menu. Added procedures to analyze the power of tests for single correlations based on the tetrachoric model, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression.
Added procedures to analyze the power of tests referring to single correlations based on the tetrachoric model, comparisons of dependent correlations, bivariate linear regression, multiple linear regression based on the random predictor model, logistic regression, and Poisson regression.
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