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THE HAGUE Authentic Jonathan Allen Jersey , Nov. 26 (Xinhua) -- The top seven of the Dutch topflight all enjoyed a win in the 13th match round of theEredivisie.

League leaders PSV beat Excelsior 2-1 in Rotterdam on Sunday. Anown goal by Jurgen Mattheij and the 10th goal of the season byEredivisie top scorer Hirving Lozano handed PSV a 2-0 lead athalf-time. PSV had trouble in a lackluster second half, with RyanKoolwijk scoring for the home-team, but did not give away the threepoints.

Also on Sunday Ajax came 1-0 behind through a Chris Kum goalagainst Roda JC Kerkrade, but Justin Kluivert lead the home team toa 5-1 win. The son of former Ajax player Patrick Kluivert producedthe equalizer at the stroke of half time and added two more in thesecond half. Kasper Dolberg and Donny van de Beek also scored andhalf time substitute Frenkie de Jong produced three assists.

Reigning champions Feyenoord ended a winless streak of fivematches with a 2-0 victory at FC Groningen on Saturday. TonnyVilhena and Nicolai Jorgensen scored in the second half.

FC Utrecht beat Sparta 3-1 in Rotterdam on Sunday, Vitessedefeated ADO Den Haag 2-0 Authentic Derrius Guice Jersey , while PEC Zwolle won 2-1 at scHeerenveen on Saturday and AZ beat FC Twente 2-0 in Alkmaar onFriday.

The difference on top of the Eredivisie table remained unchangedwith PSV leading with 36 points from 13 match rounds, followed byAjax (28 points), AZ (28), PEC Zwolle (25), FC Utrecht (23) Authentic Da'Ron Payne Jersey ,Vitesse (22) and Feyenoord (22).

The concept of error is central throughout all statistical work. Whenever there is a measurement, inference or decision making, the possibility of error is present. So, we have to deal with errors of measurement, errors of inference and decision making.

It is useful to distinguish the two types of errors that may be present in statistical measurements Josh Doctson Jersey , namely, systematic errors and random errors. Systematic errors are also called as non sampling errors and the random errors are also called sampling errors. The systematic errors as the term implies, causes a measurement to be incorrect in some systematic way. They are the errors involved in the procedures of a statistical investigation and may occur in the planning stages or during or after the collection process. Examples of cause of systematic error (or bias) are faulty design of a questionnaire (such as misleading or ambiguous questions) systematic mistakes in planning and carrying out the collection and processing of the data, non response and refusals by respondents to provide information and a great discrepancy between the sampling frame and the target Universe. If observations have arisen from a sample drawn from a statistical universe, systematic errors are those that persist even when the sampling size is increased. As a generalization Troy Apke Jersey , these errors may be viewed as arising primarily from inaccuracies or deficiencies in the measuring instrument.

On the other hand, random errors or sampling errors may be viewed as arising from the operation of a large number of uncontrolled factors, conveniently described by the term: chance. As an example of this type of error, if repeated random samples of the same size are drawn from a statistical universe (with replacement of each sample after it is drawn) than a particular statistic, such as the arithmetic mean Geron Christian Jersey , will differ from sample to sample. These sample menus tend to distribute themselves below and above the true population parameter (arithmetic mean), with small deviations between the statistics and the parameter occurring relatively frequently and large deviations occurring relatively infrequently.

The word: “true” has quotation marks around it because it refers to the figure that would have been obtained through deviations occurring relatively infrequently. The word: “true” has quotation marks around it because it refers to the figure that would have been obtained through complete coverage of the universe. The difference between the mean of a particular sample and the population mean is said to be random error (or sampling error). The complete collection of factors that could explain why the sample mean differed from the population mean is unknown., but we can conveniently sum them up altogether and refer to the difference as a random or chance error.

Random errors are those that arise from differences found between the outcomes of trials (or samples) and the corresponding universe value using the same measurement procedures and instruments. The sizes of the differences indicate the reliability or precision. Random errors decrease on the average as sample size increases. It is precisely for this reason that people prefer a large sample of observations to a small one, all other things being equal; that is, since sampling errors are on the average smaller for large samples Preston Smith Jersey , the results are more reliable or more precise.
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