Quantitative Data Analysis for Information Science Professionals

2020 ◽  
pp. 349-372
Author(s):  
Regis Chireshe
Keyword(s):  
Data Analysis ◽  
Literature Review ◽  
Quantitative Data ◽  
Information Science ◽  
Analysis Software ◽  
Advantages And Disadvantages ◽  
Analysis Methods ◽  
Quantitative Data Analysis ◽  
General Aspects ◽  
Data Analysis Methods

The chapter presents general aspects of quantitative data analysis as they relate to information sciences. The chapter is based on a literature review. It begins with explaining the meaning of data and quantitative data. Kinds of quantitative data are presented. The meaning of data analysis and the reasons for data analysis are also discussed. Reasons for quantitative data analysis are also discussed. The ‘what' and ‘why' of statistics in general and for information science researchers in particular is also presented. The chapter also presents the main issues of quantitative data analysis. Steps in quantitative data analysis are also presented. Preparation of quantitative data analysis is followed by a presentation on quantitative data analysis methods. The chapter highlights the popular quantitative data analysis software. A brief presentation on how quantitative data are presented and interpreted is given. The chapter ends with a discussion on the advantages and disadvantages of quantitative data analysis.

scholarly journals Quantitative data analysis methods for bead-based DNA hybridization assays using generic flow cytometry platforms

2008 ◽  
Vol 73A (5) ◽  
pp. 467-476 ◽  
Author(s):  
S. R. Corrie ◽  
G. A. Lawrie ◽  
B. J. Battersby ◽  
K. Ford ◽  
A. Rühmann ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Data Analysis ◽  
Dna Hybridization ◽  
Quantitative Data ◽  
Analysis Methods ◽  
Quantitative Data Analysis ◽  
Data Analysis Methods ◽  
Hybridization Assays

scholarly journals Analisis Loan To Deposit Ratio (LDR) Dan Non Performing Loan (NPL) Pada PT. Bank Negara Indonesia 1946 (Persero) Tbk

2021 ◽  
Author(s):  
Yolanda Tri Marta Fitri ◽  
jhon fernos
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Evaluation Criteria ◽  
Average Value ◽  
Analysis Methods ◽  
Quantitative Data Analysis ◽  
Data Analysis Methods

The purpose of this study is to determine the analysis of Loan to Deposit Ratio (LDR) and Non Performing Loans (NPL) at PT. Bank Negara Indonesia 1946 (Persero) Tbk. In analyzing the data, the authors used quantitative data analysis methods. Quantitative data is information data that is expressed in the form of figures from the calculation and measurement of the Loan To Deposit Ratio (LDR) and Non Performing Loan (NPL) analysis at PT. Bank Negara Indonesia 1946 (Persero) Tbk. The results of this study indicate that in the period 2017 - 2019 the Loan Deposit to Ratio (LDR) from the evaluation results is quite healthy because the average value is 89% with the evaluation criteria matrix is in the position > 75% LDR <100% and Non Performing Loans (NPL evaluation results are classified as healthy because NPL <5%.

scholarly journals ANALISIS PENDAPATAN PETANI KELAPA DI KELURAHAN BENGKOL KOTA MANADO (INCOME ANALYSIS OF COCONUT FARMERS IN THE SUB-DISTRICT OF BENGKOL MANADO CITY)

2021 ◽  
Vol 17 (1) ◽  
pp. 29
Author(s):  
Indriani ., Limbe ◽  
Celsius Talumingan ◽  
Caroline Betsi Diana Pakasi
Keyword(s):  
Data Analysis ◽  
Quantitative Data ◽  
Average Income ◽  
Purposive Sampling ◽  
Income Category ◽  
Analysis Methods ◽  
Quantitative Data Analysis ◽  
Data Analysis Methods

The purpose of this study was to analyze the income of farmers in Bengkol Village, Manado City. Quantitative data analysis methods to determine the income of coconut farmers in Bengkol Village. The number of respondents 20 0 the sampling was done deliberately (purposive sampling). The results showed that the average income category of farmers who own land and sell coconuts in the form of copra is Rp. 15.654.536 categories of farmers who own land and sell coconuts in the form of coconuts Rp. 773,400 and for the category of farmers who do not own land but have capital to sell coconuts in the form of copra and coconuts Rp. 7,330,500

scholarly journals ANALISIS LOAN TO DEPOSIT RATIO DAN NON PERFOMING LOAN PADA PT. BANK PEMBANGUNAN DAERAH (BPD) SUMATERA BARAT CABANG UTAMA PADANG

2019 ◽  
Author(s):  
Helmi Yati ◽  
Afriyeni Afriyeni
Keyword(s):  
Data Analysis ◽  
Regional Development ◽  
Quantitative Data ◽  
Research Results ◽  
Analysis Methods ◽  
Measurement Analysis ◽  
Quantitative Data Analysis ◽  
Data Analysis Methods ◽  
Research Show

The purpose of this research is to expand credit insights into particularly in terms of how the analysis of the Loan To Deposit Ratio (LDR) and Non were Perfoming Loan (NPL) on PT. BPD Sumatera Barat is the main branch of the field. In analyzing the data, the authors use quantitative data analysis methods. Quantitative data data is information that is stated in the form the results of calculation and measurement analysis of the Loan To Deposit Ratio and Non-Performing Loan on the regional development of PT. BPD Sumatra Barat. The results of this research show that the Loan To Deposit Ratio (LDR) on PT. BPD Sumatera Barat is the main branch of the field during the period of research results is very good because it does not exceed the maximum limits set by Bank Indonesia 110%.

Unsupervised Data Analysis Methods used in Qualitative and Quantitative Metabolomics and Metabonomics

2011 ◽  
pp. 1-28
Author(s):  
Miroslava Cuperlovic-Culf
Keyword(s):  
Data Analysis ◽  
Large Set ◽  
High Throughput Analysis ◽  
Metabolomics Data ◽  
Qualitative And Quantitative ◽  
Quantitative Metabolomics ◽  
Advantages And Disadvantages ◽  
Unsupervised Analysis ◽  
Analysis Methods ◽  
Data Analysis Methods

Metabolomics or metababonomics is one of the major high throughput analysis methods that endeavors holistic measurement of metabolic profiles of biological systems. Data analysis approaches in metabolomics can broadly be divided into qualitative – analysis of spectral data and quantitative – analysis of individual metabolite concentrations. In this work, the author will demonstrate the benefits and limitations of different unsupervised analysis tools currently utilized in qualitative and quantitative metabolomics data analysis. Following a detailed literature review outlining different applications of unsupervised methods in metabolomics, the author shows examples of an application of the major previously utilized unsupervised analysis methods. The testing of these methods was performed using qualitative as well as corresponding quantitative metabolite data derived to represent a large set of 2,000 objects. Spectra of mixtures were obtained from different combinations of experimental NMR measurements of 13 prevalent metabolites at five different groups of concentrations representing different phenotypes. The analysis shows advantages and disadvantages of standard tools when applied specifically to metabolomics.

scholarly journals A Systematic Literature Review of Intelligent Data Analysis Methods for Smart Sport Training

2020 ◽  
Vol 10 (9) ◽  
pp. 3013
Author(s):  
Alen Rajšp ◽  
Iztok Fister
Keyword(s):  
Data Analysis ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Intelligent Data Analysis ◽  
Way Of Life ◽  
Sport Training ◽  
Analysis Methods ◽  
The Internet Of Things ◽  
Data Analysis Methods ◽  
The Way

The rapid transformation of our communities and our way of life due to modern technologies has impacted sports as well. Artificial intelligence, computational intelligence, data mining, the Internet of Things (IoT), and machine learning have had a profound effect on the way we do things. These technologies have brought changes to the way we watch, play, compete, and also train sports. What was once simply training is now a combination of smart IoT sensors, cameras, algorithms, and systems just to achieve a new peak: The optimum one. This paper provides a systematic literature review of smart sport training, presenting 109 identified studies. Intelligent data analysis methods are presented, which are currently used in the field of Smart Sport Training (SST). Sport domains in which SST is already used are presented, and phases of training are identified, together with the maturity of SST methods. Finally, future directions of research are proposed in the emerging field of SST.

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