The construction of histograms from sample data
| dc.contributor.email | paul.kruger@up.ac.za | |
| dc.contributor.upauthor | Kruger, P.S. (Paul Stephanus), 1944- | |
| dc.date.accessioned | 2008-07-16T07:12:58Z | |
| dc.date.available | 2008-07-16T07:12:58Z | |
| dc.date.created | 2008-07-13 | |
| dc.date.issued | 2008-07-16T07:12:58Z | |
| dc.description | Microsoft Excel Spreadsheet with interactive hyperlinks and activities. | en |
| dc.description.abstract | A Histogram is one of the most important tools of descriptive statistics. It provides a Graphical estimation of the Distribution and Statistical Characteristics of the underlying stochastic process from which the sample has been taken. Whenever one is faced with a data set, consisting of n unordered observations from a stable stochastic process, the construction of a histogram should be one of the very first steps in the process of analyzing the data. If the sample size is small it may be difficult to obtain a useful histogram. The choice of the number of intervals, interval size, location and the range is the user's responsibility. | en |
| dc.format.extent | 428544 bytes | |
| dc.format.mimetype | application/vnd.ms-excel | |
| dc.identifier.uri | http://hdl.handle.net/2263/6162 | |
| dc.language.iso | en | en |
| dc.rights | University of Pretoria | en |
| dc.subject | Cumulative histogram | en |
| dc.subject | Construction of histograms | en |
| dc.subject | Class intervals | en |
| dc.subject | Sample size | en |
| dc.subject | Distribution function | en |
| dc.subject | Cumulative distribution | en |
| dc.subject | Percentiles | en |
| dc.subject | e-Stats | |
| dc.subject.lcsh | Autocorrelation (Statistics) | |
| dc.subject.lcsh | Cumulants | |
| dc.subject.lcsh | Statistics -- Data processing | |
| dc.subject.lcsh | Sampling (Statistics) | |
| dc.title | The construction of histograms from sample data | en |
| dc.type | Learning Object | en |