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descriptive statistics

   Also found in: Dictionary/thesaurus, Legal, Encyclopedia, Wikipedia 0.01 sec.
descriptive statistics,
statistics that measure and describe characteristics of groups without drawing inferences about the population in general.

statistics,
n the branch of mathematics that gathers, arranges, condenses, coordinates, and mathematically manipulates obtained facts so that the numerical relationships between those facts may be seen clearly and freed from anomalies resulting from chance factors.
statistics, descriptive,
n.pl the statistics used to describe only the observed group or sample from which they were derived; summary statistics such as percent, averages, and measures of variability that are computed on a particular group of individuals.
statistics, inference,
n.pl the inferences made regarding characteristics or general principles about an unseen population based on the characteristics of the observed sample. Statistical findings from a sample are generalized to pertain to the entire population. The process of drawing inferences, making predictions, and testing significance are examples of inferential statistics.
statistics, nonparametric,
n.pl the sta-tistical methods used when the statistician cannot assume that the variable being studied is normally distributed in a population. Also called
distribution-free statistics.

descriptive statistics


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They focus on the use of SPSS, a computer package for data analyses; provide an overview of the program and basic statistical concepts; and cover descriptive statistics, comparing means, ANOVA, correlation analysis, multiple and logistics regression, factor analysis and testing scale reliability, and advanced data handling, illustrating the use of SPSS through examples using version 16.
Descriptive Statistics deals with the methods of organization, reduction, summarization and presentation of data in order to make them amenable to rational analysis and interpretations.
The author provides a review on the fundamentals of statistics and food science terminology before discussing data collection methods, descriptive statistics, significance testing and experimental design.
 
 
 
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