Sentence examples for implemented statistics from inspiring English sources
The phrase 'implemented statistics' is correct and usable in written English
This phrase may be used when referring to the process of putting statistics into practice, such as when analyzing data from an experiment. For example, "The team implemented statistics to determine the success of their marketing campaign."
We test all implemented statistics on an artificial data set, somewhat similar to Tompa et al. [20], in order to control all variables.
2.3 we describe the implemented statistics routines.
EGN also implements statistics describing genetic diversity in these samples, for various user-defined thresholds of similarities.
Stephen Peckham, director and professor of health policy at Kent University's centre for health service studies, said: "Water fluoridation was implemented before statistics had been compiled on its safety or effectiveness.
We therefore implemented robust statistics (as an optional feature) by removing a certain percentage of the extreme values before the average is taken.
POTION first tries to calculate q-values using the qvalue method as described in [ 25] and implemented in Statistics:Multtest Perl module, estimating the proportion of true null hypotheses using a bootstrap procedure.
These studies did not implement standard statistics used to estimate LRLs that have long been endorsed by the International Federation of Clinical Chemistry (IFCC) and the Clinical and Laboratory Standards Institute (CLSI) [ 19- 25].
We implemented the new statistics in Figure 5 N. "Statistical analysis uses a one way ANOVA (*** P=0.0001; **** P<0.0001).
Instead of the above ordinary T-statistics, regularized T-statistics, implemented in R package st, are also included in our deGPS.
In both cases the survey was approved as part of the national survey implemented by BPS-Statistics Indonesia, the national statistics organization of the Government of Indonesia.
In particular, Kitchin (2014: 34) has highlighted how data infrastructures implemented by national statistics agencies often depend on interoperable software, shared services, analysis tools such as data visualizations, shared policies, and strong rules relating to data standardization, data quality and compliance, which 'enable data to be distributed, linked together and analysed.'.
