856 Words4 Pages

CHAPTER II
LITERATURE STUDY
2.1 Statistic Statistics comes from Latin “ Ratio Status” in Italian same words with “ Region in state”. The term emerged in early middle ages, the usual is used to express the things that relate to the study of the state. Then develop the term “ Statistics ” meaning people who in the state of affairs of the state or country expert. The methodology claimed that statistics is a branch of mathematics concerned with the collection, classification, analysis and interpretation of numerical facts, statistics can be developed for interpreting and drawing conclusions from collected data. Everything that deals even remotely with the collection, processing, interpretation and presentation of data belongs to the domain of statistics. In applying statistic for example an*…show more content…*

These sample are considered to be free lance of one another. So if an person is in one sample, then it has the same likelihood of being in the next sample that is taken. The theory of sampling is to get as much information as possible, ideally the whole of the information about the population from which the sample has been drawn. Recall that inferential statistics concern generalizing from a sample to apopulation. A critical part of inferential statistics involves determining how far sample statistics are likely to vary from each other and from the population parameter. (In this example, the sample statistics are the sample means and the population parameter is the population mean.) As the later portions of this chapter show, these determinations are based on sampling distributions.The remaining sections of the chapter concern the sampling distributions of important statistics: the Sampling Distribution of the Mean, the Sampling Distribution of the Difference Between Means, the Sampling Distribution of r, and the Sampling Distribution of a

These sample are considered to be free lance of one another. So if an person is in one sample, then it has the same likelihood of being in the next sample that is taken. The theory of sampling is to get as much information as possible, ideally the whole of the information about the population from which the sample has been drawn. Recall that inferential statistics concern generalizing from a sample to apopulation. A critical part of inferential statistics involves determining how far sample statistics are likely to vary from each other and from the population parameter. (In this example, the sample statistics are the sample means and the population parameter is the population mean.) As the later portions of this chapter show, these determinations are based on sampling distributions.The remaining sections of the chapter concern the sampling distributions of important statistics: the Sampling Distribution of the Mean, the Sampling Distribution of the Difference Between Means, the Sampling Distribution of r, and the Sampling Distribution of a

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