Sentence examples for as statistics that from inspiring English sources

Exact(3)

"With many of them in the early stages of their careers, they go for it". As any manager would, Robinson does not consider the Orioles fortunate, citing the nagging type of ailments (like center fielder Brady Anderson's ingrown toenail that forced him to miss several games) as statistics that do not appear on the disabled list.

Eligible research studies comprising a common dependent variable as well as statistics that can be transformed into effect sizes were systematically surveyed.

Units have different capabilities, as well as statistics that determine their mobility, firepower, vulnerability and other gameplay factors.

Similar(57)

The identities of these 1,873 differentially expressed genes as well as the LIMMA statistics that support their identification are provided in Table S1.

Along the way, Mr. Fitzsimmons, the dean, consults what are called "ethnic stats," which he defines as "any statistics that would give us a sense of where we are in the class regarding ethnicity at that moment". Ethnicity is one of many factors considered in a lop, Mr. Fitzsimmons said in his deposition.

(2010), we used summary statistics as test statistics that were not used for model selection or parameter estimation in previous ABC treatments (Table S11).

The school district's budget numbers are as impressive as the statistics that Daniel has put up for Missouri this season.

We've visualised their numbers below as well as a few other statistics that give context to the issue.

That's why the state's Department of Motor Vehicles, citing statistics that show as many as 1,000 daily incidents of drivers breaking the law called "Stop on Signal," has begun a program to try to curb the problems.

Welner went on to discuss recidivism among released Gitmo detainees, citing widely discredited (PDF) Pentagon statistics that claim as many as 20percentt of released Gitmo detainees have returned to terrorism.

O'Keefe's formula for pinpointing averageness is as follows: find statistics that reflect majority preferences and apply them to a given population, winnowing the pool until only one candidate remains — a perfect match.

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