MAIN POINTS IN STATISICAL DATA ANALYSIS

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GERAMI A.

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ISSN: 2588-4824

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Journal: Iranian Journal of Crop Sciences Year:2000 | Volume:2 | Issue:1 Page(s): 30-38

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Information Journal Paper

Title

MAIN POINTS IN STATISICAL DATA ANALYSIS

Author(s)

GERAMI A. | Issue Writer Certificate

Keywords

MOMENTSQ4

VARIANCE HETEROGENEITYQ4

TRANSFORMATIONQ4

NORMALITYQ4

NEAREST NEIGHBOURQ4

Abstract

Data analysis are usually based on a statistical model, which itself has some components. The most important components are, mathematical formula which relates the variable of interest to those factors which have influence on the value of that variable and controlled by the experimenter besides uncontrolled terms which are called nuisance factors. The second component are assumptions related to some factors which are important issues in data analysis. These assumptions are mainly concerned about the 1st and the 2nd MOMENTS of random factors as well as their distributions. Many data analysts do not consider these components and any result obtained without checking the validation of these components mayor may not be valid. This paper highlights these components and provide ways to check their validities.

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APA: Copy

GERAMI, A.. (2000). MAIN POINTS IN STATISICAL DATA ANALYSIS. IRANIAN JOURNAL OF CROP SCIENCES, 2(1), 30-38. SID. https://sid.ir/paper/57400/en

Vancouver: Copy

GERAMI A.. MAIN POINTS IN STATISICAL DATA ANALYSIS. IRANIAN JOURNAL OF CROP SCIENCES[Internet]. 2000;2(1):30-38. Available from: https://sid.ir/paper/57400/en

IEEE: Copy

A. GERAMI, “MAIN POINTS IN STATISICAL DATA ANALYSIS,” IRANIAN JOURNAL OF CROP SCIENCES, vol. 2, no. 1, pp. 30–38, 2000, [Online]. Available: https://sid.ir/paper/57400/en

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