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Journal articles on the topic 'ANALYZING DATA'

Author: Grafiati
Published: 11 September 2023

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1

Suganthi, R., and P. Kamalakannan. "Analyzing Stock Market Data Using Clustering Algorithm." International Journal of Future Computer and Communication 4, no. 2 (April 2015): 108–11. http://dx.doi.org/10.7763/ijfcc.2015.v4.366.

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2

Harper, Douglas, Michael S. Ball, and Gregory W. H. Smith. "Analyzing Visual Data." Contemporary Sociology 22, no. 4 (July 1993): 619. http://dx.doi.org/10.2307/2074468.

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3

Maxwell, Scott E., and Norman Cliff. "Analyzing Multivariate Data." Journal of the American Statistical Association 83, no. 404 (December 1988): 1214. http://dx.doi.org/10.2307/2290163.

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4

Wasserman, Stanley. "Analyzing Categorical Data." American Statistician 60, no. 3 (August 2006): 291–92. http://dx.doi.org/10.1198/tas.2006.s52.

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5

Katsaounis, Tena I. "Analyzing Multivariate Data." Technometrics 46, no. 2 (May 2004): 254–55. http://dx.doi.org/10.1198/tech.2004.s798.

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6

Dasgupta, Nairanjana. "Analyzing Categorical Data." Technometrics 46, no. 2 (May 2004): 255–56. http://dx.doi.org/10.1198/tech.2004.s799.

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7

MUNRO, BARBARA HAZARD. "Analyzing Nominal Data." Clinical Nurse Specialist 3, no. 4 (1989): 176–77. http://dx.doi.org/10.1097/00002800-198900340-00004.

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8

Batenkov, Dmitry. "Analyzing EEG data." XRDS: Crossroads, The ACM Magazine for Students 18, no. 1 (September 2011): 36–37. http://dx.doi.org/10.1145/2000775.2000788.

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9

Goth, Gregory. "Analyzing medical data." Communications of the ACM 55, no. 6 (June 2012): 13–15. http://dx.doi.org/10.1145/2184319.2184324.

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10

Biemann, Torsten, and Deepak K. Datta. "Analyzing Sequence Data." Organizational Research Methods 17, no. 1 (September 5, 2013): 51–76. http://dx.doi.org/10.1177/1094428113499408.

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11

LeCompte, Margaret D. "Analyzing Qualitative Data." Theory Into Practice 39, no. 3 (August 2000): 146–54. http://dx.doi.org/10.1207/s15430421tip3903_5.

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12

Kaye, Stephen B., and William F. Harris. "Analyzing refractive data." Journal of Cataract & Refractive Surgery 28, no. 12 (December 2002): 2109–16. http://dx.doi.org/10.1016/s0886-3350(02)01639-5.

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13

Borror, Connie M. "Analyzing Multivariate Data." Journal of Quality Technology 35, no. 4 (October 2003): 426–27. http://dx.doi.org/10.1080/00224065.2003.11980240.

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14

Alpins, Noel. "Analyzing refractive data." Journal of Cataract & Refractive Surgery 30, no. 2 (February 2004): 291–92. http://dx.doi.org/10.1016/j.jcrs.2004.01.010.

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15

Kaye, Stephen B., and William F. Harris. "Analyzing refractive data." Journal of Cataract & Refractive Surgery 30, no. 2 (February 2004): 292. http://dx.doi.org/10.1016/j.jcrs.2004.01.011.

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16

Hung, Jui-Hung, and Zhiping Weng. "Analyzing Microarray Data." Cold Spring Harbor Protocols 2017, no. 3 (August 29, 2016): pdb.prot093112. http://dx.doi.org/10.1101/pdb.prot093112.

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17

Jones, Thomas A. "Analyzing Categorical Data." Mathematical Geology 37, no. 2 (February 2005): 223–25. http://dx.doi.org/10.1007/s11004-005-1311-8.

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18

Frankel, Sherman. "Analyzing finasteride data." Neurourology and Urodynamics 14, no. 6 (1995): 619–24. http://dx.doi.org/10.1002/nau.1930140603.

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19

S., Sabitha, Gayathri M., and Nithya Kalyani Dr.S. "Heuristics Approach for Analyzing the Geo-Distributed Data." Bonfring International Journal of Software Engineering and Soft Computing 8, no. 1 (March 30, 2018): 01–05. http://dx.doi.org/10.9756/bijsesc.8380.

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20

Subbarao, Anusuyah. "TOWARDS ANALYZING QUALITATIVE DATA." Science Proceedings Series 1, no. 2 (April 24, 2019): 66–68. http://dx.doi.org/10.31580/sps.v1i2.640.

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Managing a software project at distributed sites which is called as Global Software Engineering (GSE) are very challenging compared to managing a project at collocated site. There are many contributing factors which makes the coordination as a big challenge in GSE because of the software project is developed across the countries and the team members are segregated all over the world (da Silva, Costa, Franca, & Prikladinicki, 2010). Therefore, projects that are developed in GSE needs more extensive coordination. Many models have been developed to overcome the coordination challenges in GSE. Despite of having numerous models in GSE, to the best of researcher’s knowledge there is no model to assess the coordination procedures in GSE projects. Thus, at the end of the research, the researchers proposed an Evaluation Model to assess the coordination procedures effectively in GSE projects. So to formulate this model, one of the research objective is to identify the coordination approaches and related indicators in GSE from the real GSE project practitioners, this is done through qualitative analysis using Nvivo.
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21

McIntosh, Allen A. "Analyzing Telephone Network Data." Journal of Computational and Graphical Statistics 8, no. 3 (September 1999): 611. http://dx.doi.org/10.2307/1390879.

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22

Gilks, Walter R., Sheila M. Gore, and Benjamin A. Bradley. "ANALYZING TRANSPLANT SURVIVAL DATA." Transplantation 42, no. 1 (July 1986): 46–49. http://dx.doi.org/10.1097/00007890-198607000-00009.

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23

Höfling, Volkmar, Karin Schermelleh-Engel, and Helfried Moosbrugger. "Analyzing Multitrait-Multimethod Data." Methodology 5, no. 3 (January 2009): 99–111. http://dx.doi.org/10.1027/1614-2241.5.3.99.

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Assessing construct validity is a core task in psychology. Since Campbell and Fiske’s (1959) seminal article on multitrait-multimethod (MTMM) analysis, several different methodological approaches for the analysis of convergent and discriminant validity of MTMM data have been developed. In this article, two MTMM approaches are transferred to the general framework of confirmatory factor analysis and compared with the extended version of the correlated trait-correlated method minus one model ( Nussbeck, Eid, Geiser, Courvoisier, & Lischetzke, 2009 ): The multilevel MTMM model ( Maas, Lensvelt-Mulders, & Hox, 2009 ) and the three-mode model ( Oort, 2009 ). Assessing the construct validity of a German Big Five MTMM data set these three MTMM approaches are compared with regard to convergent and discriminant validity estimates and with regard to method effects. Advantages and limitations of each methodological approach will be discussed in detail.
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24

Cote, Joseph A., Hoi K. Suen, and Donald Ary. "Analyzing Behavioral Observation Data." Journal of Marketing Research 27, no. 4 (November 1990): 502. http://dx.doi.org/10.2307/3172640.

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25

Green, Paul E., Eun Sul Lee, Ronald N. Forthofer, and Ronald J. Lorimar. "Analyzing Complex Survey Data." Journal of Marketing Research 28, no. 4 (November 1991): 502. http://dx.doi.org/10.2307/3172794.

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26

Swenson, Michael J., Eun Sul Lee, Ronald N. Forthofer, and Ronald J. Lorimor. "Analyzing Complex Survey Data." Journal of Marketing Research 27, no. 2 (May 1990): 241. http://dx.doi.org/10.2307/3172853.

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27

Whittemore, Alice S. "Analyzing Cohort Mortality Data." American Statistician 39, no. 4 (November 1985): 437. http://dx.doi.org/10.2307/2683027.

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28

Beck, E. M., and Stewart E. Tolnay. "Analyzing Historical Count Data." Historical Methods: A Journal of Quantitative and Interdisciplinary History 28, no. 3 (June 1995): 125–31. http://dx.doi.org/10.1080/01615440.1995.9956360.

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29

Whittemore, Alice S. "Analyzing Cohort Mortality Data." American Statistician 39, no. 4 (November 1985): 437–41. http://dx.doi.org/10.1080/00031305.1985.10479480.

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30

Taubes, G. "McGill: analyzing the data." Science 268, no. 5218 (June 23, 1995): 1714. http://dx.doi.org/10.1126/science.7605516.

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31

McIntosh, Allen A. "Analyzing Telephone Network Data." Journal of Computational and Graphical Statistics 8, no. 3 (September 1999): 611–19. http://dx.doi.org/10.1080/10618600.1999.10474836.

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32

Talja, Sanna. "Analyzing Qualitative Interview Data." Library & Information Science Research 21, no. 4 (November 1999): 459–77. http://dx.doi.org/10.1016/s0740-8188(99)00024-9.

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33

Hayes, Jack P., and J. Scott Shonkwiler. "Analyzing Mass-Independent Data." Physiological Zoology 69, no. 4 (July 1996): 974–80. http://dx.doi.org/10.1086/physzool.69.4.30164238.

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34

Yannaros, Nikos. "Analyzing Incomplete Count Data." Statistician 42, no. 2 (1993): 181. http://dx.doi.org/10.2307/2348982.

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35

Arnold, Gerald K., Eun Sul Lee, Ronald N. Forthofer, and Ronald J. Lorimor. "Analyzing Complex Survey Data." Journal of Educational Statistics 17, no. 3 (1992): 270. http://dx.doi.org/10.2307/1165150.

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36

Hall, Michelle. "Analyzing Single-Case Data." Contemporary Psychology: A Journal of Reviews 39, no. 2 (February 1994): 222–23. http://dx.doi.org/10.1037/033944.

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37

Rodgers-Farmer, A. Y., and D. Davis. "Analyzing complex survey data." Social Work Research 25, no. 3 (September 1, 2001): 185–92. http://dx.doi.org/10.1093/swr/25.3.185.

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38

Kalaivani, S., B. Priyadharshini, and B. Selva Nalini. "Analyzing Student’s Academic Performance Based on Data Mining Approach." International Journal of Innovative Research in Computer Science & Technology 5, no. 1 (January 31, 2017): 194–97. http://dx.doi.org/10.21276/ijircst.2017.5.1.4.

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39

Raiyani, Ronak S., Dr Bankim Radadiya, and Dr Satish Thumar. "Analyzing, Developing and Implementing Data Mining Techniques on Databases, Web Contents and Textual Data." Paripex - Indian Journal Of Research 2, no. 3 (January 15, 2012): 48–50. http://dx.doi.org/10.15373/22501991/mar2013/18.

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40

Venkateswara Reddy, R., and Dr D. Murali. "Analyzing Indian healthcare data with big data." International Journal of Engineering & Technology 7, no. 3.29 (August 24, 2018): 88. http://dx.doi.org/10.14419/ijet.v7i3.29.18467.

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Big Data is the enormous amounts of data, being generated at present times. Organizations are using this Big Data to analyze and predict the future to make profits and gain competitive edge in the market. Big Data analytics has been adopted into almost every field, retail, banking, governance and healthcare. Big Data can be used for analyzing healthcare data for better planning and better decision making which lead to improved healthcare standards. In this paper, Indian health data from 1950 to 2015 are analyzed using various queries. This healthcare generates the considerable amount of heterogeneous data. But without the right methods for data analysis, these data have become useless. The Big Data analysis with Hadoop plays an active role in performing significant real-time analyzes of the enormous amount of data and able to predict emergency situations before this happens.
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41

Gu, Zhen. "Accurate Data Process for Analyzing Nanopore Data." Biophysical Journal 110, no. 3 (February 2016): 407a. http://dx.doi.org/10.1016/j.bpj.2015.11.2199.

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42

Malarmangai, T. "Analyzing the Data in Hospital." International Journal for Research in Applied Science and Engineering Technology V, no. IV (April 26, 2017): 747–48. http://dx.doi.org/10.22214/ijraset.2017.4135.

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43

Navarro, Diego, and Steve Juggins. "Analyzing paleolimnological data with R." PAGES news 21, no. 2 (August 2013): 85. http://dx.doi.org/10.22498/pages.21.2.85.

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44

Fox, Andrea, Marica Manisera, Marco Sandri, and Paola Zuccolotto. "Analyzing Basketball Data with BasketballAnalyzeR." CHANCE 35, no. 3 (July 3, 2022): 42–56. http://dx.doi.org/10.1080/09332480.2022.2123161.

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45

Patch, Steven, S. Maxwell, and H. Delaney. "Designing Experiments and Analyzing Data." Technometrics 33, no. 3 (August 1991): 375. http://dx.doi.org/10.2307/1268809.

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46

Stevens, Jill. "Activities: Generating and Analyzing Data." Mathematics Teacher 86, no. 6 (September 1993): 475–89. http://dx.doi.org/10.5951/mt.86.6.0475.

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47

Seiyama, Kazuo. "Significance of Analyzing the Data." Kazoku syakaigaku kenkyu 17, no. 1 (2005): 10–14. http://dx.doi.org/10.4234/jjoffamilysociology.17.10.

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48

LaVange, Lisa M., Hoi K. Suen, and Donald Ary. "Analyzing Quantitative Behavioral Observation Data." Journal of the American Statistical Association 85, no. 409 (March 1990): 268. http://dx.doi.org/10.2307/2289578.

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49

Hamerle, A., H. K. Suen, and D. Ary. "Analyzing Quantitative Behavioral Observation Data." Biometrics 48, no. 1 (March 1992): 330. http://dx.doi.org/10.2307/2532763.

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50

Attaf, Sarah, Nadjia Benblidia, and Omar Boussaid. "Warehousing and Analyzing Textual Data." International Journal of Mathematical Modelling and Numerical Optimisation 8, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijmmno.2017.10006816.

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