Sentence examples for tables to predict from inspiring English sources

Christopher Columbus used astronomical tables to predict the lunar eclipse of 1 March 1504 and used this knowledge to persuade the natives of Jamaica to continue to provide him and his crew with food, telling them that the eclipse was a sign from God.

However, the original reason why this conception received a dominant position was not the lack of realization that more complex forest structures and dynamics are naturally common, but rather the necessity to adopt a sufficiently simple conceptual model that could be used to organize rational forest management and for example to construct forest yield tables to predict forest growth.

We applied statistical testing in 3-way contingency tables to predict TF interactions.

Different authors have described reference equations and tables to predict the 6MWT-distance in healthy elderly subjects.

48 49 Our analytical approach used official life tables to predict mortality accurately but was limited by the lack of accessible and reliable age and gender specific estimates of survival by health and partnership status.

Moyers [ 5] recommended using the 75th percentile level of probability in his tables to predict mesio-distal widths of un-erupted permanent teeth, however, previous studies showed that Moyers' probability tables are not an accurate method for the prediction of mesio-distal widths of un-erupted permanent teeth in different populations [ 18- 28, 30- 36].

For years, the highlight of the meal has been a game in which servers ask someone at your table to predict the number on a chip pulled from a bowl.

Table 4 Linear mixed-effects model (ANOVA table) to predict the remaining massof Fagus sylvatica, Picea abies and Pinus sylvestris Source Sum of Squares df F Sig. Eta squared Decomp.

Mendeleev was not the first chemist to do so, but he was the first to be recognized as using the trends in his periodic table to predict the properties of those missing elements, such as gallium and germanium.

The regression provided weights for the basicity calculation function and decision table to predict which segregation region best models a given peptide bond.

For the second step we used the multi-cohort proportional multi-state life table model to predict changes in health-adjusted life years and health care costs as a function of changes in PA.