scholarly journals Experimental design and primary data analysis methods for comparing adaptive interventions.

2012 ◽  
Vol 17 (4) ◽  
pp. 457-477 ◽  
Author(s):  
Inbal Nahum-Shani ◽  
Min Qian ◽  
Daniel Almirall ◽  
William E. Pelham ◽  
Beth Gnagy ◽  
...  
1970 ◽  
Vol 6 ◽  
pp. 98-108
Author(s):  
Bal K Joshi ◽  
Madhusudan P Upadhyay ◽  
Hari P Bimb ◽  
D Gauchan ◽  
BK Baniya

Synthesizing data analysis methods adopted under in situ global project in Nepal along withvariables and nature of study could be guiding reference for researchers especially to those involvedin on farm research. The review work was conducted with the objective to help in utilizing andmanaging in situ database system. The objectives of the experiment, the structure of the treatmentsand the experimental design used primarily determine the type of analysis. There were 60 papers ofthis project published in Nepal. All these papers are grouped under 8 thematic groups namely 1.Agroecosystem (3 papers), 2. Agromorphological and farmers’ perception (7 papers), 3. Croppopulation structure (5 papers), 4. Gender, policy and general (15 papers), 5. Isozyme andmolecular (6 papers), 6. Seed systems and farmers’ networks (5 papers), 7. Social, cultural andeconomical (11 papers) and 8. Value addition (8 papers). All these papers were reviewed basicallyfor data type, sample size, sampling methods, statistical methods and tools, varieties and purposes.Descriptive and inferential statistics along with multivariate methods were commonly used in onfarm research. Experimental design, the most common in on station trial was least used. Study overspace and time was not adopted. There were 5 kinds of data generated, 45 statistical tools adoptedin eight different crop species. Among the 5 kinds of data under these eight subject areas,categorical type was highest followed by discrete numerical. Binary type was least in frequency.Most of the papers were related to rice followed by taro and finger millet. Cucumber and pigeonpea were studied least. Descriptive statistics along with Χ2, multivariate analysis and regressionapproaches would be appropriate tools. Similarly SPSS and MINITAB may be good software. Thebest one among a number of statistical tools should be selected and utmost care must be exercisedwhile collecting data.Key words: Data analysis methods; on farm research; on station research; subject areasDOI: 10.3126/narj.v6i0.3371Nepal Agriculture Research Journal Vol.6 2005 pp.98-108


2019 ◽  
Vol 6 (1) ◽  
pp. 1-11
Author(s):  
Hasemi Fauzi Ma’mun ◽  
Dedeng Abdul Gani Amruloh ◽  
Amna Mawardi

The purpose of this study is to determine the effect of creativity on the performance of SMEs. Population in this research is all of micro enterprise in templek stone industry in Purwakarta, number of sample used in this research is 21 micro enterprise, all member of population is used as sample. Primary data obtained through the distribution of questionnaires to the respondents ie owners or managers of SMEs, while secondary data obtained from BPS and other relevant agencies related to research, data analysis methods used in this study is multiple linear regression with the help of the program IBM SPSS version 23 . Based on the results of research and testing has been done show that partially creativity significantly influence the performance of SMEs templek stone, furthermore, the results of research and testing of psychological capital variable is known to have a partial influence not significant to performance, simultaneously or creativity and psychological capital have a positive and significant effect on the performance of Batu Templek micro enterprise in Purwakarta.


2020 ◽  
Vol 5 (2) ◽  
pp. 219-228
Author(s):  
Edy Sudaryanto

This study aims to identify and analyze opportunities, challenges, constraints and efforts of vocational high school or Sekolah Menengah Kejuruan (SMK) to create graduates especially accounting programs that are able to manage village funds. The object of the study are accounting program students of SMK PGRI 2 Cibinong. Data used in this study are primary data and secondary data. Data is collected using interviews, observation, and documentation. Data analysis methods use data reduction, data display and conclusion drawing/verification. The results of this study show that the SMK PGRI 2 Cibinong Bogor aware of the opportunities for SMK graduates of the accounting program to fill the scarcity of skilled human resources to manage village funds. But teachers have less experience in the practice of village fund accounting so that they do not have confidence in  teaching. Other constraints are less discussion of government accounting in the accounting syllabus and the absence of a standard handbook/module for teachers to teach accounting subjects.


2017 ◽  
Vol 9 (33) ◽  
pp. 4783-4789 ◽  
Author(s):  
Samuel Mabbott ◽  
Yun Xu ◽  
Royston Goodacre

Reproducibility of SERS signal acquired from thin films developed in-house and commercially has been assessed using seven data analysis methods.


2010 ◽  
Vol 58 (2) ◽  
pp. e22-e23
Author(s):  
Karen A. Monsen ◽  
Karen S. Martin ◽  
Bonnie L Westra

2010 ◽  
Vol 19 (8) ◽  
pp. 996 ◽  
Author(s):  
Philip E. Higuera ◽  
Daniel G. Gavin ◽  
Patrick J. Bartlein ◽  
Douglas J. Hallett

Over the past several decades, high-resolution sediment–charcoal records have been increasingly used to reconstruct local fire history. Data analysis methods usually involve a decomposition that detrends a charcoal series and then applies a threshold value to isolate individual peaks, which are interpreted as fire episodes. Despite the proliferation of these studies, methods have evolved largely in the absence of a thorough statistical framework. We describe eight alternative decomposition models (four detrending methods used with two threshold-determination methods) and evaluate their sensitivity to a set of known parameters integrated into simulated charcoal records. Results indicate that the combination of a globally defined threshold with specific detrending methods can produce strongly biased results, depending on whether or not variance in a charcoal record is stationary through time. These biases are largely eliminated by using a locally defined threshold, which adapts to changes in variability throughout a charcoal record. Applying the alternative decomposition methods on three previously published charcoal records largely supports our conclusions from simulated records. We also present a minimum-count test for empirical records, which reduces the likelihood of false positives when charcoal counts are low. We conclude by discussing how to evaluate when peak detection methods are warranted with a given sediment–charcoal record.


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