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Journal articles on the topic 'Standard deviation'

Author: Grafiati
Published: 4 June 2021
Last updated: 22 February 2023

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1

Holyoake, Dean, Brid Hehir, and Chris Buswell. "Standard deviation." Nursing Standard 13, no. 32 (April 28, 1999): 22–23. http://dx.doi.org/10.7748/ns.13.32.22.s43.

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2

Leonidas, J. C. "Standard deviation vs. standard error." Journal of Ultrasound in Medicine 5, no. 5 (May 1986): 294. http://dx.doi.org/10.7863/jum.1986.5.5.294.

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3

Sedgwick, P. "Standard deviation versus standard error." BMJ 343, dec13 3 (December 13, 2011): d8010. http://dx.doi.org/10.1136/bmj.d8010.

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4

Hoffman, Julien I. E. "Standard Error or Standard Deviation?" Pediatric Cardiology 36, no. 5 (April 2, 2015): 1105–6. http://dx.doi.org/10.1007/s00246-015-1166-9.

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5

Hanchett, Marilyn. "Understanding Standard Deviation." Journal of the Association for Vascular Access 9, no. 3 (September 1, 2004): 164–65. http://dx.doi.org/10.2309/1552-8855-9.3.164.

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6

BOYD, A. V. "The Standard Deviation and Absolute Deviations from the Mean." Teaching Statistics 7, no. 3 (September 1985): 78–81. http://dx.doi.org/10.1111/j.1467-9639.1985.tb00590.x.

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7

Sharma, SR, and Ravi Datt. "SOME ELEMENTARY INEQUALITIES BETWEEN MEAN AND STANDARD DEVIATION." Mathematical Journal of Interdisciplinary Sciences 4, no. 1 (September 1, 2015): 23–28. http://dx.doi.org/10.15415/mjis.2015.41003.

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8

Takeishi, S., and T. Inoue. "IDF21-0083 Standard deviation." Diabetes Research and Clinical Practice 186 (April 2022): 109311. http://dx.doi.org/10.1016/j.diabres.2022.109311.

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9

Duffield, Timothy J., S. Camille Peres, William Amonette, and Paul Ritchey. "Standard Deviation of sEMG." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 57, no. 1 (September 2013): 1400–1404. http://dx.doi.org/10.1177/1541931213571313.

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10

Edelmann, Dominic, Donald Richards, and Daniel Vogel. "The distance standard deviation." Annals of Statistics 48, no. 6 (December 2020): 3395–416. http://dx.doi.org/10.1214/19-aos1935.

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11

Wu, Mingxin, and Yijun Zuo. "Trimmed and winsorized standard deviations based on a scaled deviation." Journal of Nonparametric Statistics 20, no. 4 (May 2008): 319–35. http://dx.doi.org/10.1080/10485250802036909.

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12

Newberger, Florence, Alan M. Safer, and Saleem Watson. "What is "Standard" About the Standard Deviation." Missouri Journal of Mathematical Sciences 22, no. 2 (May 2010): 86–90. http://dx.doi.org/10.35834/mjms/1312233137.

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13

Biau, David J. "In Brief: Standard Deviation and Standard Error." Clinical Orthopaedics and Related Research® 469, no. 9 (May 10, 2011): 2661–64. http://dx.doi.org/10.1007/s11999-011-1908-9.

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14

Carter, Rickey E. "A Standard Error: Distinguishing Standard Deviation From Standard Error." Diabetes 62, no. 8 (July 23, 2013): e15-e15. http://dx.doi.org/10.2337/db13-0692.

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15

Wang, Chun, Yi Zheng, and Hua-Hua Chang. "Does Standard Deviation Matter? Using “Standard Deviation” to Quantify Security of Multistage Testing." Psychometrika 79, no. 1 (December 10, 2013): 154–74. http://dx.doi.org/10.1007/s11336-013-9356-y.

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16

Quan, Hui, and Ji Zhang. "Estimate of standard deviation for a log-transformed variable using arithmetic means and standard deviations." Statistics in Medicine 22, no. 17 (2003): 2723–36. http://dx.doi.org/10.1002/sim.1525.

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17

Reichenstein, William R. "On standard deviation and risk." Journal of Portfolio Management 13, no. 2 (January 31, 1987): 39–40. http://dx.doi.org/10.3905/jpm.1987.409093.

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18

Majumder, Arindam, and Abhishek Majumder. "Standard Deviation Method Based PSO." International Journal of Swarm Intelligence Research 7, no. 2 (April 2016): 15–35. http://dx.doi.org/10.4018/ijsir.2016040102.

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Nowadays, optimization of process parameters in manufacturing process deals with a number of objectives. However, the optimization of such process becomes more complex if selected attributes are conflicting in nature. Therefore, to overcome this problem in this study a SDM based PSO algorithm is proposed for optimizing the manufacturing process having multi attribute. In this proposed approach the SDM is used to convert multi attributes into single attribute, named as multi performance index, while the optimal value of this multi performance index is predicted by PSO. Finally, three instances related to optimization of advanced manufacturing process parameters are solved by the proposed approach and are compared with the results of the other established optimization techniques such as Desirability based RSM, SDM-GA and SDM-CACO. From the comparison it has been revealed that the proposed approach performs better as compare to the existing approaches.
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19

Choi, S. W., and G. T. C. Wong. "It's just a standard deviation!" Anaesthesia 71, no. 8 (June 14, 2016): 969–71. http://dx.doi.org/10.1111/anae.13565.

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20

Lee, Dong Kyu, Junyong In, and Sangseok Lee. "Standard deviation and standard error of the mean." Korean Journal of Anesthesiology 68, no. 3 (2015): 220. http://dx.doi.org/10.4097/kjae.2015.68.3.220.

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21

Hassani, H., M. Ghodsi, and G. Howell. "A note on standard deviation and standard error." Teaching Mathematics and its Applications 29, no. 2 (March 12, 2010): 108–12. http://dx.doi.org/10.1093/teamat/hrq003.

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22

Tillotson, Malcolm. "Standard error of the mean or standard deviation?" Clinical Biomechanics 6, no. 4 (November 1991): 195. http://dx.doi.org/10.1016/0268-0033(91)90046-s.

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23

Thomas, Ravi, Padma Paul, and Jayaprakash Muliyil. "Use of Pattern Standard Deviation Instead of Corrected Pattern Standard Deviation in Andersonʼs Criteria." Journal of Glaucoma 9, no. 6 (December 2000): 480–82. http://dx.doi.org/10.1097/00061198-200012000-00010.

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24

Parrill, Fey, Alison McKim, and Kimberly Grogan. "Gesturing standard deviation: Gestures undergraduate students use in describing their concepts of standard deviation." Journal of Mathematical Behavior 53 (March 2019): 1–12. http://dx.doi.org/10.1016/j.jmathb.2018.05.003.

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25

Ang, James S., Gwoduan David Jou, and Tsong-Yue Lai. "Alternative Formulas to Compute Implied Standard Deviation." Review of Pacific Basin Financial Markets and Policies 12, no. 02 (June 2009): 159–76. http://dx.doi.org/10.1142/s0219091509001599.

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We assume that the call option's value is correctly priced by Black and Scholes' option pricing model in this paper. This paper derives an exact closed-form solution for implied standard deviation under the condition that the underlying asset price equals the present value of the exercise price. The exact closed-form solution provides the true implied standard deviation and has no estimate error. This paper also develops three alternative formulas to estimate the implied standard deviation if this condition is violated. Application of the Taylor expansion on a single call option value derives the first formula. The accuracy of this formula depends on the deviation between the underlying asset price and the present value of the exercise price. Use of the Taylor formula on two call option prices with different exercise prices is used to develop the second formula, which can be used even though the underlying asset price deviates significantly from the present value of the exercise price. Extension of the second formula's approach to third options value derives the third formula. A merit of the third formula is to circumvent a required parameter used in the second formula. Simulations demonstrate that the implied standard deviations calculated by the second and third formulas provide accurate estimates of the true implied standard deviations.
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26

Macaskill, Petra. "Standard deviation and standard error: interpretation, usage and reporting." Medical Journal of Australia 208, no. 2 (February 2018): 63–64. http://dx.doi.org/10.5694/mja17.00633.

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27

Kay, Bartholomew. "The ongoing discussion regarding standard deviation and standard error." Advances in Physiology Education 32, no. 4 (December 2008): 334. http://dx.doi.org/10.1152/advan.90191.2008.

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28

Sedgwick, P. "Standard deviation or the standard error of the mean." BMJ 350, feb17 1 (February 17, 2015): h831. http://dx.doi.org/10.1136/bmj.h831.

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29

Sarkar, Jyotirmoy, and Mamunur Rashid. "Have You Seen the Standard Deviation?" Nepalese Journal of Statistics 3 (September 16, 2019): 1–10. http://dx.doi.org/10.3126/njs.v3i0.25574.

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Background: Sarkar and Rashid (2016a) introduced a geometric way to visualize the mean based on either the empirical cumulative distribution function of raw data, or the cumulative histogram of tabular data. Objective: Here, we extend the geometric method to visualize measures of spread such as the mean deviation, the root mean squared deviation and the standard deviation of similar data. Materials and Methods: We utilized elementary high school geometric method and the graph of a quadratic transformation. Results: We obtain concrete depictions of various measures of spread. Conclusion: We anticipate such visualizations will help readers understand, distinguish and remember these concepts.
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30

Williams, W., and H. Dillon. "Hearing protector performance and standard deviation." Noise and Health 7, no. 28 (2005): 51. http://dx.doi.org/10.4103/1463-1741.31629.

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31

FARNUM, N. R., and R. C. SUICH. "Bounds on the Sample Standard Deviation." Teaching Statistics 9, no. 2 (May 1987): 51–56. http://dx.doi.org/10.1111/j.1467-9639.1987.tb00832.x.

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32

Feuerman, Martin. "Standard deviation of a temperature coefficient." International Journal of Mathematical Education in Science and Technology 21, no. 6 (November 1990): 963–66. http://dx.doi.org/10.1080/0020739900210614.

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33

Braithwaite, Susan Shapiro. "Multiplicative Standard Deviation for Blood Glucose." Diabetes Technology & Therapeutics 16, no. 4 (April 2014): 195–97. http://dx.doi.org/10.1089/dia.2013.0295.

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34

Kirkwood, T. B. L. "Geometric Standard Deviation - Reply to Bohidar." Drug Development and Industrial Pharmacy 19, no. 3 (January 1993): 395–96. http://dx.doi.org/10.3109/03639049309038775.

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35

Elseviers, Monique M., and Maurice Harrington. "STATISTICS CORNER THE MYSTERIOUS STANDARD DEVIATION." EDTNA-ERCA Journal 29, no. 2 (April 6, 2003): 101–3. http://dx.doi.org/10.1111/j.1755-6686.2003.tb00283.x.

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36

Wang, Chunlin, Jianyong Sun, Wanjin Xu, and Xiaolin Chen. "Depth Learning Standard Deviation Loss Function." Journal of Physics: Conference Series 1176 (March 2019): 032050. http://dx.doi.org/10.1088/1742-6596/1176/3/032050.

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37

Ost, Ben, Anuj Gangopadhyaya, and Jeffrey C. Schiman. "Comparing standard deviation effects across contexts." Education Economics 25, no. 3 (June 30, 2016): 251–65. http://dx.doi.org/10.1080/09645292.2016.1203868.

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38

Schoonhoven, Marit, and Ronald J. M. M. Does. "A Robust Standard Deviation Control Chart." Technometrics 54, no. 1 (February 2012): 73–82. http://dx.doi.org/10.1080/00401706.2012.648869.

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39

Streiner, David L. "Maintaining Standards: Differences between the Standard Deviation and Standard Error, and When to Use Each." Canadian Journal of Psychiatry 41, no. 8 (October 1996): 498–502. http://dx.doi.org/10.1177/070674379604100805.

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Many people confuse the standard deviation (SD) and the standard error of the mean (SE) and are unsure which, if either, to use in presenting data in graphical or tabular form. The SD is an index of the variability of the original data points and should be reported in all studies. The SE reflects the variability of the mean values, as if the study were repeated a large number of times. By itself, the SE is not particularly useful; however, it is used in constructing 95% and 99% confidence intervals (CIs), which indicate a range of values within which the “true” value lies. The CI shows the reader how accurate the estimates of the population values actually are. If graphs are used, error bars equal to plus and minus 2 SEs (which show the 95% CI) should be drawn around mean values. Both statistical significance testing and CIs are useful because they assist the reader in determining the meaning of the findings.
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40

Curran-Everett, Douglas. "Explorations in statistics: standard deviations and standard errors." Advances in Physiology Education 32, no. 3 (September 2008): 203–8. http://dx.doi.org/10.1152/advan.90123.2008.

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Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This series in Advances in Physiology Education provides an opportunity to do just that: we will investigate basic concepts in statistics using the free software package R. Because this series uses R solely as a vehicle with which to explore basic concepts in statistics, I provide the requisite R commands. In this inaugural paper we explore the essential distinction between standard deviation and standard error: a standard deviation estimates the variability among sample observations whereas a standard error of the mean estimates the variability among theoretical sample means. If we fail to report the standard deviation, then we fail to fully report our data. Because it incorporates information about sample size, the standard error of the mean is a misguided estimate of variability among observations. Instead, the standard error of the mean provides an estimate of the uncertainty of the true value of the population mean.
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41

Denneberg, Dieter. "Premium Calculation: Why Standard Deviation Should be Replaced by Absolute Deviation." ASTIN Bulletin 20, no. 2 (November 1990): 181–90. http://dx.doi.org/10.2143/ast.20.2.2005441.

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AbstractAverage absolute (instead of quadratic) deviation from median (instead of expectation) is better suited to determine the safety loading for insurance premiums than standard deviation: The corresponding premium functionals behave additive under the practically relevant risk sharing schemes between first insurer and reinsurer.
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42

Nadurak, Vitaliy. "Why Moral Heuristics can Lead to Mistaken Moral Judgments." KRITERION – Journal of Philosophy 34, no. 1 (January 1, 2020): 99–113. http://dx.doi.org/10.1515/krt-2020-340106.

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Abstract Given the lack of generally accepted moral standards, one of the controversial questions for those who investigate moral heuristics is whether we can argue that moral heuristics can lead to mistaken moral judgments. This paper suggests that, even if we agree that moral standards are different and chosen subjectively, deviations from them are possible and we can prove such deviations in a logically correct way. However, in this case, it must be admitted that not every deviation is a mistake. Deviation becomes a mistake only when a person departs from the standard which she or he considers as right. There are cases where it is impossible to establish the fact of a mistake: when a person chooses a moral standard post hoc, in the light of which the decision would be right (only when there is a deviation from all moral standards which a person considers as right, it is possible to recognize the decision as mistaken). Accepting the idea of the subjectivity of a moral standard, it is also necessary to accept the idea of relativity of moral heuristics: the normative standard chosen by a person also determines which method of moral decision making will be considered as a heuristic.
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43

DELMAS, ROBERT, and YAN LIU. "EXPLORING STUDENTS’ CONCEPTIONS OF THE STANDARD DEVIATION." STATISTICS EDUCATION RESEARCH JOURNAL 4, no. 1 (May 29, 2005): 55–82. http://dx.doi.org/10.52041/serj.v4i1.525.

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This study investigated introductory statistics students’ conceptual understanding of the standard deviation. A computer environment was designed to promote students’ ability to coordinate characteristics of variation of values about the mean with the size of the standard deviation as a measure of that variation. Twelve students participated in an interview divided into two primary phases, an exploration phase where students rearranged histogram bars to produce the largest and smallest standard deviation, and a testing phase where students compared the sizes of the standard deviation of two distributions. Analysis of data revealed conceptions and strategies that students used to construct their arrangements and make comparisons. In general, students moved from simple, one-dimensional understandings of the standard deviation that did not consider variation about the mean to more mean-centered conceptualizations that coordinated the effects of frequency (density) and deviation from the mean. Discussions of the results and implications for instruction and further research are presented. First published May 2005 at Statistics Education Research Journal: Archives
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44

Carpenter, Sharon Paul, Jane Burns, and Edward Tomaszewski. "Deviation from Standard State Noise Wall Policy." Transportation Research Record: Journal of the Transportation Research Board 2011, no. 1 (January 2007): 165–74. http://dx.doi.org/10.3141/2011-18.

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45

Hanchett, Marilyn. "Science Skills Made Easy: Understanding Standard Deviation." Journal of the Association for Vascular Access 9, no. 3 (January 2004): 164–65. http://dx.doi.org/10.2309/155288504774654856.

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46

Mohammed, Nadia, Riyam Essa, and Amina Najim. "Improved LSB Method using Standard Deviation Scale." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 1 (March 15, 2013): 195–208. http://dx.doi.org/10.33899/csmj.2013.163452.

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47

Hargreaves, George H., and Zohrab A. Samani. "Estimation of Standard Deviation of Potential Evapotranspiration." Journal of Irrigation and Drainage Engineering 114, no. 1 (February 1988): 175–80. http://dx.doi.org/10.1061/(asce)0733-9437(1988)114:1(175).

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48

Deakin, R. E., and D. G. Kildea. "A Note on Standard Deviation and RMS." Australian Surveyor 44, no. 1 (June 1999): 74–79. http://dx.doi.org/10.1080/00050351.1999.10558776.

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49

PRIDDIS, M. J. M. "An Upper Bound for the Standard Deviation." Teaching Statistics 9, no. 3 (September 1987): 78–80. http://dx.doi.org/10.1111/j.1467-9639.1987.tb00842.x.

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50

Bohidar, N. R. "Determination of Geometric Standard Deviation for Dissolution." Drug Development and Industrial Pharmacy 17, no. 10 (January 1991): 1381–87. http://dx.doi.org/10.3109/03639049109057303.

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