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Business Statistics 3rd Edition Sharpe Pdf 64
Descriptive statistics are a set of tools that provide information about a sample of the population, without prespecifying any relationship between a recognized characteristic of that population and the sample statistics. Categories of descriptive statistics are:
- Basic descriptive statistics are generally based either on a set of numerical measurements (e.g. counts, averages, variances, and standard deviations), or on a classification of the observations (e.g. Z-scores, trend charts, bar charts, pie charts, and histograms).
- Classification statistics are often used to identify observed differences between groups of observations.[1]
- Statistical hypothesis testing is the process of inferring the data-generating distribution of an observed or hypothetical set of samples. Hypothesis tests are used when the investigator wishes to infer, either with certainty or with some confidence, whether or not a hypothesized state of the world is true.
- Categorical statistics is a process that quantitatively describes a subset of an attribute space based on the value of qualitative or discrete categorical attributes. Although descriptive statistics can often be applied to quantitative data, it is not normally considered an exhaustive description, nor can it be applied to continuous data.
Inferential statistics is a tool often used in the academic and social sciences to draw conclusions about the nature of a population based on observed relationships of the observed attributes of the members (i.e., data). Common inferential statistics tools are regression analysis, survival/censoring analysis, nonparametric statistics, and multiple regression analysis.
In the data and information practice, descriptive statistics and inferential statistics are often combined, wherein a descriptive statistic, such as mean or median, is often applied to the data and visually presented, to ascertain if a few or many outliers exist or if the distribution is symmetric.
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