Variance, Standard Deviation, Standard Error, Coefficient of Variation

2012 ◽  
pp. 16-22
Keyword(s):  
Standard Deviation ◽  
Standard Error ◽  
Coefficient Of Variation ◽  
Error Coefficient

scholarly journals Comparative study of descendent colon rupture resistance considering traction force of rupture and total energy of rupture in rats

2006 ◽  
Vol 21 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Feng Chung Wu ◽  
Huei Diana Lee ◽  
Maksoel Algustin Krauspenhar Niz ◽  
Maria de Loudes Setsuko Ayrizono ◽  
Cláudio Saddy Rodrigues Coy ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Total Energy ◽  
Standard Error ◽  
Coefficient Of Variation ◽  
Traction Force ◽  
Average Standard Deviation ◽  
Linear Viscoelastic ◽  
Analysis Of Results ◽  
Version 2.0 ◽  
Analysis System

PURPOSE: To compare total energy of rupture and traction force of rupture tests within a rupture resistance study of descendent colon of rats. METHODS: Twelve descendent colon segments of rats were considered to perform the study. For each one of the specimens, total energy of rupture and traction force of rupture necessary to promote colic wall burst were evaluated through the biomechanical total energy of rupture test using the Biomechanical Data Acquisition and Analysis System, version 2.0. Average, standard deviation, standard error of average and coefficient of variation were considered for analysis of results. RESULTS: Traction force of rupture average, standard deviation, standard error of average and coefficient of variation were 380.05 gf, 98.74, 28.5 e 25.98%, respectively while total energy of rupture presented average of 244.85 gf, standard deviation of 57.76, standard error of average of 16.67 and coefficient of variation of 23.59. CONCLUSION: Although, total energy of rupture considered a larger number of attributes to its calculation related to non-linear viscoelastic materials, such as colic wall, it presented a smaller coefficient of variation when compared to traction force of rupture, thus demonstrating to constitute a possible parameter to analyze intestinal resistance of rats.

scholarly journals Eco-friendly and Economical Spectrophotometric Estimation of the Low Water-Soluble Drug (Norfloxacin) Applying the Concept of Mixed Hydrotropy

2021 ◽  
Author(s):  
Ketan Soni ◽  
Kavita Sharma
Keyword(s):  
Standard Deviation ◽  
Organic Solvents ◽  
Standard Error ◽  
Coefficient Of Variation ◽  
Dosage Forms ◽  
Water Soluble ◽  
Current Analysis ◽  
Water Soluble Drug ◽  
Water Soluble Drugs ◽  
Bulk Drug

Abstract Objectives The main aim of the research was to analyze an economical and eco-friendly approach to improve the solubility of norfloxacin. The current analysis was to utilize the hydrotropic solutions to extract the drugs from their dosage forms, avoiding the use of costlier and harmful organic solvents. Materials and Methods In this study, an ultraviolet–visible spectrophotometer (model 1800, Shimadzu Corporation) was used to analyze the norfloxacin drug. The mixed hydrotropy approach was used to determine the solubility of norfloxacin. In this work, a blend solution (20% of urea + 20% of sodium benzoate) was used as a hydrotropic solubilizing agent. Results The solubility of norfloxacin drug in water was very low at ∼0.88 mg/mL and the solubility of norfloxacin drug in the blend solution was 11 mg/mL. From 98.96 (tablet II) to 99.35 (tablet I), the percent estimation value was achieved. This value was nearly 100, so the proposed method was correct. Standard deviation (0.2540–0.4156), percentage coefficient of variation (0.2566–0.4183), and the value of standard error (0.1481–0.2415) are also very low; hence, we can say that the proposed method is accurate. Conclusion To avoid the use of organic solvents, the mixed hydrotropy concept can be used for spectrophotometric estimation of low water-soluble drugs from bulk drug samples. It provides an economical and environmentally friendly mechanism.

Improved Fluorometric Method for Determining Selenium

1978 ◽  
Vol 61 (4) ◽  
pp. 927-930 ◽  
Author(s):  
Phyllis A Whetter ◽  
Duane E Ullrey
Keyword(s):  
Skeletal Muscle ◽  
Standard Deviation ◽  
Standard Error ◽  
Coefficient Of Variation ◽  
Biological Materials ◽  
Mean Difference ◽  
Fluorometric Method ◽  
Aoac Method ◽  
The Mean ◽  
Selenium Analysis

Abstract A previously reported method for selenium analysis of biological materials has been modified to reduce equipment requirements and labor, resulting in 40—80 determinations in an 8-hr period. Digestions are performed on hot plates in Erlenmeyer flasks, and neutralization, chelation with EDTA, complexing with 2,3- diaminonaphthalene, and extraction of the piazoselenol into cyclohexane are completed in the same vessel. Flotation of the cyclohexane layer into the neck of the flask with water allows convenient transfer to fluorometer tubes. Representative analytical values for serum, skeletal muscle, liver, kidney, corn, and alfalfa hay are presented. The mean recovery (± standard deviation) of added selenite selenium in 84 determinations was 98.1±7.1%. The mean coefficient of variation (± standard error) of repeated analyses of the same samples was 6.98±0.78%. The mean difference (± standard error) between values determined by the proposed method and the AOAC method was -0.03±0.60%.

scholarly journals An alternative to the rejection of observations

1932 ◽  
Vol 137 (831) ◽  
pp. 78-87 ◽  
Keyword(s):  
Standard Deviation ◽  
Continuous Function ◽  
Large Deviations ◽  
Opposite Direction ◽  
Standard Error ◽  
The Other ◽  
Cause Of Error ◽  
The Mean ◽  
Normal Law ◽  
Usual Rule

1. It is widely felt that any method of rejecting observations with large deviations from the mean is open to some suspicion. Suppose that by some criterion, such as Peirce’s and Chauvenet’s, we decide to reject observations with deviations greater than 4 σ, where σ is the standard error, computed from the standard deviation by the usual rule; then we reject an observation deviating by 4·5 σ, and thereby alter the mean by about 4·5 σ/ n , where n is the number of observations, and at the same time we reduce the computed standard error. This may lead to the rejection of another observation deviating from the original mean by less than 4 σ, and if the process is repeated the mean may be shifted so much as to lead to doubt as to whether it is really sufficiently representative of the observations. In many cases, where we suspect that some abnormal cause has affected a fraction of the observations, there is a legitimate doubt as to whether it has affected a particular observation. Suppose that we have 50 observations. Then there is an even chance, according to the normal law, of a deviation exceeding 2·33 σ. But a deviation of 3 σ or more is not impossible, and if we make a mistake in rejecting it the mean of the remainder is not the most probable value. On the other hand, an observation deviating by only 2 σ may be affected by an abnormal cause of error, and then we should err in retaining it, even though no existing rule will instruct us to reject such an observation. It seems clear that the probability that a given observation has been affected by an abnormal cause of error is a continuous function of the deviation; it is never certain or impossible that it has been so affected, and a process that completely rejects certain observations, while retaining with full weight others with comparable deviations, possibly in the opposite direction, is unsatisfactory in principle.

Interpretation of the Standard Error of Measurement when True Scores and Error Scores on Mental Tests are Not Independent

1966 ◽  
Vol 19 (2) ◽  
pp. 611-617 ◽  
Author(s):  
Donald W. Zimmerman ◽  
Richard H. Williams
Keyword(s):  
Standard Deviation ◽  
Standard Error ◽  
Test Score ◽  
Test Reliability ◽  
True Score ◽  
Observed Score ◽  
Standard Error Of Measurement ◽  
True Scores ◽  
Modified Equation ◽  
Error Of Measurement

It is shown that for the case of non-independence of true scores and error scores interpretation of the standard error of measurement is modified in two ways. First, the standard deviation of the distribution of error scores is given by a modified equation. Second, the confidence interval for true score varies with the individual's observed score. It is shown that the equation, so=√[(N−O/a]+[so2(roō−roo)/roō]̄, where N is the number of items, O is the individual's observed score, a is the number of choices per item, so2 is observed variance, roo is test reliability as empirically determined, and roō is reliability for the case where only non-independent error is present, provides a more accurate interpretation of the test score of an individual.

scholarly journals Classification of the coefficient of variation to variables in beef cattle experiments

2017 ◽  
Vol 47 (11) ◽  
Author(s):  
Marcos André Braz Vaz ◽  
Paulo Santana Pacheco ◽  
Enio Júnior Seidel ◽  
Angela Pellegrin Ansuj
Keyword(s):  
Standard Deviation ◽  
Beef Cattle ◽  
Coefficient Of Variation ◽  
Theses And Dissertations

ABSTRACT: This research was conducted to propose a classification of the coefficient of variation (CV%) in many categories of variables of production and carcass of beef cattle experiments. The data was collected from theses and dissertations. We used the methods of classification considering mean and standard deviation, and considering median and pseudo-sigma. The two methods showed similar results so both can be used to classify CV%. We propose only three categories to rank CV%: low, medium and high.

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