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Section of statistics, dedicated to processing of small samples (2 ≤ n <20), conventionally called micro-statistical.
The reduction came mostly from North American and Central American tourists, according the Visit Guatemala Flash Report in the Investigations of Market Section of Statistics.
According to the Visit Guatemala Flash Report in the Investigations of Market Section of Statistics: "The main indicators for measuring tourism in Guatemala show that despite the negative factors affecting the sector worldwide (economic crisis, unemployment, etc).
The Visit Guatemala Flash Report in the Investigations of Market Section of Statistics reported the number of tourists coming to Guatemala rose from 1,776,868 to 1,875,777 tourists - up 5.6% from the previous year.
For example, the Visit Guatemala Flash Report in the Investigations of Market Section of Statistics found: "For the month of December 2010, Guatemala had a total of 173,537 visitors... a decline of 7.9% from December 2009".
"This result reinforces the trend estimates of the recovery made by the World Tourism Organization, WTO, and which the Commission considers that the arrival of international tourism will increase between 5% and 6%," the Visit Guatemala Flash Report in the Investigations of Market Section of Statistics reported.
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This statistic corresponds to the "Poisson data with Poisson background (cstat)" section of the Statistics in XSPEC appendix, which includes the equations used to define the statistic.
This statistic corresponds to the "Poisson data (cstat)" section of the Statistics in XSPEC appendix.
More importantly, by definition, n-gram models only take into account strings of adjacent words, whereas as argued in Section 2.3, statistics of co-occurrences of words that are physically distant but syntactically close can be very useful to capture related concepts.
In this section, the statistics of the period-3 values computed from a training set of exon sequences and intron sequences are used to define the threshold values of two novel thresholding methods to classify an untrained sequence to be either an exon sequence or an intron sequence.
Bottom section: Summary statistics of the distributions' within-individual averages To compare the accuracy of horizontal and vertical tracking, the test retest means of the respective components for gain and RMS errors were plotted for each individual (Fig. 2).
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