Demographic Methods across the Tree of Life

2021 ◽  
Keyword(s):  
Data Collection ◽  
Quantitative Methods ◽  
Population Models ◽  
Tree Of Life ◽  
Bank Loans ◽  
Matrix Population Models ◽  
Individual Based Models ◽  
Demographic Methods ◽  
Methods Analytical ◽  
Analytical Approaches

Demography is everywhere in our lives: from birth to death. Demography shapes our daily decisions, as well as the decisions that others make on us (e.g. bank loans, retirement age). Demography is everywhere across the Tree of Life. The universal currencies of demography—survival, development, reproduction, and recruitment—shape the performance of all species, from lions to dandelions. The omnipresence of demography in all things alive and dead, and its multiple applications to better understand the ecology, evolution, and conservation/management of species, allows us to—in principle—apply the wide array of quantitative methods to, for example, bacteria or humans. However, demographic methods to date have remained taxonomically siloed, despite the fact that, to a large extent, they are widely applicable across the Tree of Life. In this book, we walk nonexperts through the ABCs of data collection, model construction, analyses, and interpretation across a wide repertoire of demographic artillery. This book introduces the reader to some of the demographic methods, including abundance-based models, life tables, matrix population models, integral projection models, integrated population models, and individual based models, to mention a few. Through the careful integration of data collection methods, analytical approaches, and applications, clearly guided through fully reproducible R scripts, we provide a state-of-the-art thorough representation of many of the most popular tools that any demographer (or demographically inclined mind) should equip themselves with.

The Status of Livelihood Vulnerability and Its CopingCapacities of Urban Squatters in Kathmandu Metropolitan City, Nepal

Patan Pragya ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 19-32
Author(s):  
Chhabi Ram Baral
Keyword(s):  
Data Collection ◽  
Urban Area ◽  
Urban Areas ◽  
Quantitative Methods ◽  
Urban Poverty ◽  
Rural Poverty ◽  
Poor People ◽  
Qualitative And Quantitative ◽  
Qualitative And Quantitative Methods ◽  
The Status

Urban poverty is one of multidimensional issue in Nepal. Increasing immigration from the outer parts of Kathmandu due to rural poverty, unemployment and weak security of the lives and the properties are core causes pushing people into urban areas. In this context how squatter urban area people sustain their livelihoods is major concern. The objectives of the study are to find out livelihood assets and capacities squatters coping with their livelihood vulnerability in adverse situation. Both qualitative and quantitative methods are applied for data collection. It is found that squatters social security is weak, victimized by severe health problems earning is not regular with lack of physical facilities and overall livelihood is critical. This study helps to understand what the changes that have occurred in livelihood patterns and how poor people survive in urban area.

Climate change heats matrix population models

2013 ◽  
Vol 82 (6) ◽  
pp. 1117-1119 ◽  
Author(s):  
Salvador Herrando-Pérez
Keyword(s):  
Climate Change ◽  
Population Models ◽  
Matrix Population Models

scholarly journals Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Verónica Lloréns-Rico ◽  
Sara Vieira-Silva ◽  
Pedro J. Gonçalves ◽  
Gwen Falony ◽  
Jeroen Raes
Keyword(s):  
Microbial Communities ◽  
Quantitative Methods ◽  
Microbial Load ◽  
Metagenomic Sequencing ◽  
Sampling Depth ◽  
Microbiome Research ◽  
Microbiome Data ◽  
The Impact ◽  
Analytical Approaches ◽  
Quantitative Approaches

AbstractWhile metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

PENGARUH PERSONAL SELLING TERHADAP PENCAPAIAN TARGET PENJUALAN (STUDI KASUS PT. SETIAWAN SEDJATI)

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Ranty Octavianita ◽  
Eki Dudi Darmawan
Keyword(s):  
Data Collection ◽  
Correlation Coefficient ◽  
Research Method ◽  
Quantitative Methods ◽  
Personal Selling ◽  
Strong Relationship ◽  
Regression Equation ◽  
T Test ◽  
Coefficient Of Determination ◽  
Sample Data

The existence of instability in the value of sales is an important evaluation that must be carried out by management. The purpose of this study is to determine the effect of Personal Selling on Sales Targets at PT. Setiawan Sedjati. The location of data collection is done at PT. Setiawan Sedjati Bandung. The research method uses quantitative methods. This research is a descriptive correlation with sample data collection using the Slovin formula. A total of 67 respondents were used as samples in this study consisting of employees of the marketing division and customers of PT. Setiawan Sedjati. The existing samples were then processed using SPSS Statistic Software version 26. Based on the processed data, the results of the regression equation Y = 20.478 + 0.182x. Then the correlation coefficient value of 0.747, it can be said that these results have a strong relationship between variables. The value of the coefficient of determination is 55.8%. The calculated value of 9.068 > 2.6512 this result shows a significant increase between variables on the t-test. It can be concluded that H1 accepted and H0 rejected, namely the variable personal selling. The variable personal selling has an influence on sales.

scholarly journals Cost Budget Variance

2021 ◽  
Vol 9 (1) ◽  
pp. 60-64
Author(s):  
Seto Sulaksono Adi Wibowo ◽  
Dwi Amelia Putri ◽  
Yosi Handayani
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Quantitative Methods ◽  
Fiscal Year ◽  
Budget Management ◽  
Time Service ◽  
Knowing How ◽  
Engineering Department ◽  
The Difference ◽  
Collection Methods

The research was conducted at the Scanner Engineering Department of PT Epson Batam. The topic is written about budget management for repair and maintenance (die & mold) costs with the aim of knowing how to minimize the variance between budgeted costs and their realization. Data collection methods used in this study were interviews, observation, and documentation, and descriptive and quantitative methods were used for data analysis. The existing budgeting system in the Scanner Engineering Department has been carried out correctly and effectively met the objectives, but overall during the 2018 fiscal year there were budget inefficiencies. Based on observations, it is known that from the budget made there are still differences (favorable variance and unfavorable variance). Where the difference arises due to unexpected costs for damaged equipment, the difference between the scheduled repair time (service) and the reality, as well as delays in sending invoices or debit notes.

scholarly journals The influence of organization culture on teacher performance of elementary school

2021 ◽  
Vol 6 (2) ◽  
pp. 460
Author(s):  
Ayu Tahnia ◽  
Happy Fitria ◽  
Achmad Wahidy
Keyword(s):  
Elementary School ◽  
Linear Regression ◽  
Data Collection ◽  
Multiple Linear Regression ◽  
Significant Influence ◽  
Quantitative Methods ◽  
Teacher Performance ◽  
Organization Culture ◽  
Good Organization

This study aims to discover the significant influence of Organization Culture on teacher performance in cluster 1 Rambutan Subdistrict, Banyuasin Regency . This research uses quantitative methods. Data collection techniques using questionnaires and documentation. The data was analyzed using multiple linear regression formulas.The results of this study show that there is a significant influence of Organization Culture on teacher performance of elementary school with a t count value of 4,182 and t table of 1,998 where t count > t table then Ha2 received. The conclusion of this research is that good organization culture where they would actualized teacher performance.

scholarly journals Hubungan Budaya Kerja dan Koordinasi Terhadap Kinerja Organisasi pada Badan Pengembangan Sumber Daya Manusia (BPSDM) Provinsi Jambi

2019 ◽  
Vol 4 (1) ◽  
pp. 136
Author(s):  
Enadarlita Enadarlita ◽  
Musfarita Affiani
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Organizational Performance ◽  
Quantitative Methods ◽  
Work Culture ◽  
The Relationship ◽  
Survey Approach

This study aims to analyze the magnitude of the relationship 1) work culture towards organizational performance in BPSDM Jambi Province. 2) Coordination of organizational performance in BPSDM Jambi Province. 3) Work culture and Coordination of organizational performance in BPSDM Jambi Province. This study uses quantitative methods with the type of survey approach. Data collection techniques are carried out by interviews, observations, questionnaires, and documentation. Based on the results of data analysis, the conclusions that can be drawn from this study are 1) Work culture (X1) has an influence on organizational performance because the significance value is 0.041 <0.05 and t count> t table (2.064> 1.66), meaning H0 is rejected and Ha is accepted. 2) Coordination (X2) does not have an influence on organizational performance because the value of Significance is 0.109> 0.05 and seen from the value of t count <t table (1.615 <1.66), means H0 is accepted and Ha is rejected or coordination does not have a significant effect on organizational performance. 3) Based on F count 3.091> F table (2.92) and significance 0.049 <0.05% means Ho is rejected and Ha is accepted or work culture and coordination simultaneously have an influence on organizational performance. So the conclusion is that if the work culture and coordination are carried out together well, then the organization's performance will also increase and vice versa.

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