Advanced statistical manual part i
•
0 likes•156 views
This document introduces an advanced statistical manual for Ayurveda research. It provides more advanced statistical applications, including those used in data science. The topics covered include repeated measures analysis, multiple linear regression, superiority/bioequivalence/non-inferiority trials, logistic regression, and other machine learning techniques. Examples from Ayurveda research are provided to illustrate key statistical concepts and their applications. The goal is to present concepts first, then illustrate them using real contexts in order to help students and researchers better understand and apply advanced statistics.
Report
Share
Report
Share
Recommended
Abstract: Perceptions of the Nursing Faculty Towards the Development of eTest...
The document summarizes a study on the perceptions of nursing faculty at Silliman University towards developing an eTest generator. A survey of 26 respondents found that they generally agreed with developing the eTest generator. They perceived it as useful, finding that it could improve work performance, effectiveness, productivity and quality. Respondents also perceived the eTest generator as somewhat easy to use. The study found a significant relationship between perceived usefulness and ease of use towards developing the eTest generator. Based on these positive results, the study recommends that the Silliman University College of Nursing develop and deploy an eTest generator as an eLearning tool.
Advanced statistical manual for ayurveda research sample
Glad to note that we have come up with a second statistical manual on Ayurveda research. This time, it is on more advanced forms of statistical analysis. We hope that researchers will take advantage of the information contained in this manual with interest. The presentation involves some mathematics but the concepts are described in simple terms and illustrated with examples from Ayurveda or from a more general medical context where needed.
Mission hospital package pricing analysis
Business recommendations and statistical analysis based on previous patient data using excel. Used a simple linear regression and a multiple linear regression to find out the specific quantitative relationship between the target variable and the explanatory variables. The multiple regression analysis provided insights on which explanatory variables have a major influence on the target variable, the Total Cost to the Hospital. Previous patient data was not enough to determine the cost to hospital.
Machine learning in computational docking
The document summarizes recent developments in using machine learning techniques for computational drug docking. It finds that machine learning methods, such as random forests, can more accurately predict binding affinity between proteins and ligands compared to traditional scoring functions. Specifically, the best random forest model achieved a correlation of 0.803 between predicted and experimental binding affinity, compared to 0.644 for classical scoring functions. Machine learning also more accurately ranks ligands and identifies the top binding pose. The document concludes that machine learning is better able to utilize relevant molecular features for computational drug docking compared to traditional methods.
Response to diseases: Sensitizing scientists in India for bridging leadership.
The presentation attempts to sensitize young scientists engaged with research in broader areas of disease biology and therapeutics to go beyond knowledge creation in their respective sub-domain. It urges scientists to reflect on 'bigger picture' for ownership of larger problem. This should help them to thrive for co-ownership of such problems involving related stakeholders across various disciplines in order to facilitate technological innovation. It also urges scientists to engage in 'co-creation' of responsive programme and services by ensuring institutional arrangement at various levels of value chain and empowerment of people so that they can access and use the technological solution thus developed.
See full paper at : http://dx.doi.org/10.13140/2.1.2696.3524
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah focus on diagnosis base veterinary treatment
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah
This document is an invitation from Dr. Jibachha Sah to celebrate the new year 2018 with various veterinary organizations and establishments. It lists several veterinary colleges, hospitals, laboratories, shops and encourages celebrating them by establishing diagnosis-based treatment. It offers support for setting up veterinary laboratories through training, equipment and chemicals. It also offers phone support, on-site visits and hands-on skills training for a fee. The document promotes working with the author to grow veterinary businesses through diagnosis-based treatments in 2018.
4.2 placebos & double blind
This document describes an experiment conducted by an electric company to test two approaches to encouraging energy conservation among customers: 1) providing small digital displays in households to show current electricity use and estimated monthly cost, and 2) giving customers a chart and information to monitor electricity use from their outside meter. The company will conduct an experiment comparing these two approaches to a control group that only receives general energy consumption information. The summary describes how the experiment would use a randomized design involving 60 households willing to participate, with the households randomly assigned to the three groups to compare the approaches.
Recommended
Abstract: Perceptions of the Nursing Faculty Towards the Development of eTest...
The document summarizes a study on the perceptions of nursing faculty at Silliman University towards developing an eTest generator. A survey of 26 respondents found that they generally agreed with developing the eTest generator. They perceived it as useful, finding that it could improve work performance, effectiveness, productivity and quality. Respondents also perceived the eTest generator as somewhat easy to use. The study found a significant relationship between perceived usefulness and ease of use towards developing the eTest generator. Based on these positive results, the study recommends that the Silliman University College of Nursing develop and deploy an eTest generator as an eLearning tool.
Advanced statistical manual for ayurveda research sample
Glad to note that we have come up with a second statistical manual on Ayurveda research. This time, it is on more advanced forms of statistical analysis. We hope that researchers will take advantage of the information contained in this manual with interest. The presentation involves some mathematics but the concepts are described in simple terms and illustrated with examples from Ayurveda or from a more general medical context where needed.
Mission hospital package pricing analysis
Business recommendations and statistical analysis based on previous patient data using excel. Used a simple linear regression and a multiple linear regression to find out the specific quantitative relationship between the target variable and the explanatory variables. The multiple regression analysis provided insights on which explanatory variables have a major influence on the target variable, the Total Cost to the Hospital. Previous patient data was not enough to determine the cost to hospital.
Machine learning in computational docking
The document summarizes recent developments in using machine learning techniques for computational drug docking. It finds that machine learning methods, such as random forests, can more accurately predict binding affinity between proteins and ligands compared to traditional scoring functions. Specifically, the best random forest model achieved a correlation of 0.803 between predicted and experimental binding affinity, compared to 0.644 for classical scoring functions. Machine learning also more accurately ranks ligands and identifies the top binding pose. The document concludes that machine learning is better able to utilize relevant molecular features for computational drug docking compared to traditional methods.
Response to diseases: Sensitizing scientists in India for bridging leadership.
The presentation attempts to sensitize young scientists engaged with research in broader areas of disease biology and therapeutics to go beyond knowledge creation in their respective sub-domain. It urges scientists to reflect on 'bigger picture' for ownership of larger problem. This should help them to thrive for co-ownership of such problems involving related stakeholders across various disciplines in order to facilitate technological innovation. It also urges scientists to engage in 'co-creation' of responsive programme and services by ensuring institutional arrangement at various levels of value chain and empowerment of people so that they can access and use the technological solution thus developed.
See full paper at : http://dx.doi.org/10.13140/2.1.2696.3524
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah focus on diagnosis base veterinary treatment
Celebrate 2018 with veterinary Diagnostics by Dr.Jibachha Sah
This document is an invitation from Dr. Jibachha Sah to celebrate the new year 2018 with various veterinary organizations and establishments. It lists several veterinary colleges, hospitals, laboratories, shops and encourages celebrating them by establishing diagnosis-based treatment. It offers support for setting up veterinary laboratories through training, equipment and chemicals. It also offers phone support, on-site visits and hands-on skills training for a fee. The document promotes working with the author to grow veterinary businesses through diagnosis-based treatments in 2018.
4.2 placebos & double blind
This document describes an experiment conducted by an electric company to test two approaches to encouraging energy conservation among customers: 1) providing small digital displays in households to show current electricity use and estimated monthly cost, and 2) giving customers a chart and information to monitor electricity use from their outside meter. The company will conduct an experiment comparing these two approaches to a control group that only receives general energy consumption information. The summary describes how the experiment would use a randomized design involving 60 households willing to participate, with the households randomly assigned to the three groups to compare the approaches.
Advanced Statistical Manual for Ayurveda Research
These slides covers more advanced statistical applications including that in data science.
The mode of presentation is that the concept is introduced first, followed by illustration and the use in a real context.
Advanced statistical manual part ii
This document introduces an advanced statistical manual for Ayurveda research. It summarizes 14 statistical and machine learning techniques covered in the manual, including logistic regression, decision trees, random forests, support vector machines, naive Bayes classifiers, neural networks, and K-nearest neighbors. For each technique, it provides a brief conceptual overview and an illustrative example using Ayurveda data. The goal of the manual is to cover more advanced statistical applications relevant for data science in Ayurveda research.
Stat Methods in ayurveda
The document discusses various statistical methodologies that can be applied to Ayurveda research, including experimentation, surveys, case-control studies, meta-analysis, survival studies, and time series analysis. It provides an overview of how these methods are currently used in Ayurveda research and highlights some areas that could be improved, such as employing stratification and larger sample sizes. Logistic regression and decision trees are presented as effective analytical techniques for case-control studies.
Ich sample size
This document discusses sample size calculations for clinical trials. It explains that sample size is determined by key factors like the primary variable, test statistic, null and alternative hypotheses, type I and II error rates, and variability estimates. It provides an example calculation for a trial comparing two analgesics. The document also reviews International Conference on Harmonisation guidelines on justifying sample size estimates and assumptions, investigating the sensitivity of sample size to deviations, and conventions for setting type I and II error rates.
Cost Effectiveness Analysis in Health economics
This document summarizes a web-based seminar on using cost-effectiveness analysis as a decision support tool for employers. It defines cost-effectiveness analysis as a method to compare different health interventions or programs based on their costs and outcomes. The document provides examples of how cost-effectiveness analysis can help employers make informed decisions about benefits programs and coverage options by objectively evaluating alternatives in a standardized way. It also discusses strategic considerations for interpreting and applying cost-effectiveness analyses to support evidence-based decision making.
Advanced manual part 4
This document introduces an advanced statistical manual for Ayurveda research. It summarizes 14 statistical topics covered in the manual, including stratified multistage sampling, multiple linear regression, time series analysis, and survival analysis. The goal is to incorporate modern statistical methods into Ayurveda research to help bring Ayurveda into the scientific mainstream. Training workshops are offered to help researchers apply these techniques.
Advanced Statistical Manual Part III
This document introduces an advanced statistical manual for Ayurveda research. It covers more advanced statistical applications, including those used in data science. Some of the topics covered include repeated measures analysis, multiple linear regression, classification techniques like logistic regression, decision trees, random forests, and clustering analysis. Examples of principal component analysis and cluster analysis are provided to illustrate how these techniques can be used to reduce dimensionality and classify objects respectively. The overall document provides an overview of advanced statistical topics and techniques for research in an Ayurveda context.
Assigning Scores For Ordered Categorical Responses
This document summarizes a research article that proposes a new method for assigning scores to ordered categorical response variables in statistical analysis. Specifically, it discusses the ordered stereotype model, which allows for uneven spacing between categories of an ordinal variable through estimated score parameters. The article presents simulation studies showing the disadvantages of assuming equal spacing, and applies the ordered stereotype model to a real dataset, demonstrating non-equal spacing. It also proposes a new median measure for ordinal data based on estimated score parameters from the ordered stereotype model.
Ayur data startup
AyurData is a consulting firm specialized in clinical trial design and analysis with an emphasis on Ayurveda research. The firm aims to promote scientific rigor in Ayurveda research through modern statistical standards and methods. Services include statistical support for student works and active researchers, training programs, and data analysis services. The firm reviewed current clinical research practices and statistical trends to effectively support researchers.
Value based care.
This document discusses value-based care for home healthcare providers. It defines value-based care as outcomes that matter most to patients divided by the total cost of care. This framework helps healthcare providers collaborate to maximize value for patients over their entire care cycle by measuring outcomes and costs in order to iterate and improve over time. Key aspects of implementing value-based care for home health providers include organizing care around patient conditions, measuring outcomes and costs for each patient, enabling integrated technology, and moving to bundled payments for full care cycles.
2012 NATIONAL NURSING CORE COMPETENCY STANDARDS
The document outlines the 2012 National Nursing Core Competency Standards in the Philippines. It discusses the roles of entry-level nurses including client care, leadership/management, and research. For client care, it details 5 responsibilities and corresponding performance indicators. It also outlines responsibilities and indicators for the leadership/management and research roles. The standards were developed through 10 phases including validation studies and a public hearing. They provide a framework for nursing education, licensure exams, and practice standards in the Philippines.
Services for Later Life: Are we any closer to integrating health and social c...
Presentation from Dennis L Kodner, International Visiting Fellow, The Kings Fund, Co- Director of the Aetna Foundation Care Co-ordination Study
Effective Useful Life and Persistence for Behavioral Programs and Framing the...
Presentations by Opinion Dynamics' Amanda Dwelley and Olivia Patterson from the ACEEE SEE Action Behavioral Persistence Webinar: 1.) Effective Useful Life and Persistence for Behavioral Programs 2.) Framing the Challenges Associated with Determining Effectiveness of Behavioral Programs Presentations
Ich guidelines e9 to e12
This document provides an overview of ICH guidelines E9 through E12, which provide statistical and clinical trial design guidance. E9 discusses statistical principles for clinical trials, including trial context, scope, design techniques to avoid bias, sample size considerations, and data analysis. E10 covers choice of control groups in clinical trials and describes placebo, no treatment, dose-response, and active controls. E11 provides guidance for clinical trials in pediatric patients, including issues around timing, formulations, study types, age classifications, and ethical considerations. E12 relates to clinical evaluation by therapeutic category.
Chapter 019
This document discusses evidence-based practice and strategies for synthesizing evidence, including conducting systematic reviews and meta-analyses. It describes the 10 step process for systematic reviews, which includes formulating a clinical question, searching for and selecting studies, critically appraising studies, and developing a final report. It also discusses how to conduct meta-analyses by statistically combining data from multiple studies to determine the overall effectiveness of an intervention.
Ebm misconception myths facts
This document discusses evidence-based medicine (EBM) and addresses some common misconceptions. It outlines the benefits of EBM, including that it is a rigorous, problem-solving approach that leads to better patient outcomes when the best available evidence is incorporated into clinical decision making. Some myths are addressed, such as the idea that experience is better evidence than clinical trials, or that EBM is too time consuming. The document emphasizes that EBM helps improve quality of care when combined with clinical expertise and patient preferences.
Application of EQ-5D in Reimbursement Decision Making: The Case of NICE
This document outlines how the National Institute for Health and Care Excellence (NICE) uses cost-effectiveness analysis to inform reimbursement decisions in the UK. It discusses NICE's process and how it generally accepts interventions with an incremental cost-effectiveness ratio of less than £20,000-30,000 per quality-adjusted life year (QALY). The document emphasizes the important role of the EQ-5D questionnaire in NICE's decisions by allowing comparison of health outcomes. It addresses issues like collecting EQ-5D data, mapping from other measures, and potential limitations of EQ-5D for certain conditions.
How to establish and evaluate clinical prediction models - Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modeling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
Statistical distributions
This document discusses different types of statistical distributions that are found in nature. It provides examples of normal distributions that describe many biological traits like height and IQ, which tend to form a bell curve. Income distributions often follow a lognormal pattern with most people in lower income groups. Tree diameter distributions in natural forests typically take an inverse J-shape. Population age structures also form distinctive patterns over time, like a pyramid shape in the past with high child mortality rates.
BMI
This document summarizes the findings of an online survey on obesity prevalence and factors. The survey received poor response with only 53 entries. After excluding pregnant women, there were 50 observations from people in India and other countries. 62% of participants were either overweight or obese according to BMI standards. Multiple regression analysis found that age and disease condition were significantly associated with higher BMI, while disease lowered BMI. Stress, diet, and exercise habits may also contribute to the high rates of overweight and obesity seen in the sample, though larger studies are needed to verify these relationships.
More Related Content
Similar to Advanced statistical manual part i
Advanced Statistical Manual for Ayurveda Research
These slides covers more advanced statistical applications including that in data science.
The mode of presentation is that the concept is introduced first, followed by illustration and the use in a real context.
Advanced statistical manual part ii
This document introduces an advanced statistical manual for Ayurveda research. It summarizes 14 statistical and machine learning techniques covered in the manual, including logistic regression, decision trees, random forests, support vector machines, naive Bayes classifiers, neural networks, and K-nearest neighbors. For each technique, it provides a brief conceptual overview and an illustrative example using Ayurveda data. The goal of the manual is to cover more advanced statistical applications relevant for data science in Ayurveda research.
Stat Methods in ayurveda
The document discusses various statistical methodologies that can be applied to Ayurveda research, including experimentation, surveys, case-control studies, meta-analysis, survival studies, and time series analysis. It provides an overview of how these methods are currently used in Ayurveda research and highlights some areas that could be improved, such as employing stratification and larger sample sizes. Logistic regression and decision trees are presented as effective analytical techniques for case-control studies.
Ich sample size
This document discusses sample size calculations for clinical trials. It explains that sample size is determined by key factors like the primary variable, test statistic, null and alternative hypotheses, type I and II error rates, and variability estimates. It provides an example calculation for a trial comparing two analgesics. The document also reviews International Conference on Harmonisation guidelines on justifying sample size estimates and assumptions, investigating the sensitivity of sample size to deviations, and conventions for setting type I and II error rates.
Cost Effectiveness Analysis in Health economics
This document summarizes a web-based seminar on using cost-effectiveness analysis as a decision support tool for employers. It defines cost-effectiveness analysis as a method to compare different health interventions or programs based on their costs and outcomes. The document provides examples of how cost-effectiveness analysis can help employers make informed decisions about benefits programs and coverage options by objectively evaluating alternatives in a standardized way. It also discusses strategic considerations for interpreting and applying cost-effectiveness analyses to support evidence-based decision making.
Advanced manual part 4
This document introduces an advanced statistical manual for Ayurveda research. It summarizes 14 statistical topics covered in the manual, including stratified multistage sampling, multiple linear regression, time series analysis, and survival analysis. The goal is to incorporate modern statistical methods into Ayurveda research to help bring Ayurveda into the scientific mainstream. Training workshops are offered to help researchers apply these techniques.
Advanced Statistical Manual Part III
This document introduces an advanced statistical manual for Ayurveda research. It covers more advanced statistical applications, including those used in data science. Some of the topics covered include repeated measures analysis, multiple linear regression, classification techniques like logistic regression, decision trees, random forests, and clustering analysis. Examples of principal component analysis and cluster analysis are provided to illustrate how these techniques can be used to reduce dimensionality and classify objects respectively. The overall document provides an overview of advanced statistical topics and techniques for research in an Ayurveda context.
Assigning Scores For Ordered Categorical Responses
This document summarizes a research article that proposes a new method for assigning scores to ordered categorical response variables in statistical analysis. Specifically, it discusses the ordered stereotype model, which allows for uneven spacing between categories of an ordinal variable through estimated score parameters. The article presents simulation studies showing the disadvantages of assuming equal spacing, and applies the ordered stereotype model to a real dataset, demonstrating non-equal spacing. It also proposes a new median measure for ordinal data based on estimated score parameters from the ordered stereotype model.
Ayur data startup
AyurData is a consulting firm specialized in clinical trial design and analysis with an emphasis on Ayurveda research. The firm aims to promote scientific rigor in Ayurveda research through modern statistical standards and methods. Services include statistical support for student works and active researchers, training programs, and data analysis services. The firm reviewed current clinical research practices and statistical trends to effectively support researchers.
Value based care.
This document discusses value-based care for home healthcare providers. It defines value-based care as outcomes that matter most to patients divided by the total cost of care. This framework helps healthcare providers collaborate to maximize value for patients over their entire care cycle by measuring outcomes and costs in order to iterate and improve over time. Key aspects of implementing value-based care for home health providers include organizing care around patient conditions, measuring outcomes and costs for each patient, enabling integrated technology, and moving to bundled payments for full care cycles.
2012 NATIONAL NURSING CORE COMPETENCY STANDARDS
The document outlines the 2012 National Nursing Core Competency Standards in the Philippines. It discusses the roles of entry-level nurses including client care, leadership/management, and research. For client care, it details 5 responsibilities and corresponding performance indicators. It also outlines responsibilities and indicators for the leadership/management and research roles. The standards were developed through 10 phases including validation studies and a public hearing. They provide a framework for nursing education, licensure exams, and practice standards in the Philippines.
Services for Later Life: Are we any closer to integrating health and social c...
Presentation from Dennis L Kodner, International Visiting Fellow, The Kings Fund, Co- Director of the Aetna Foundation Care Co-ordination Study
Effective Useful Life and Persistence for Behavioral Programs and Framing the...
Presentations by Opinion Dynamics' Amanda Dwelley and Olivia Patterson from the ACEEE SEE Action Behavioral Persistence Webinar: 1.) Effective Useful Life and Persistence for Behavioral Programs 2.) Framing the Challenges Associated with Determining Effectiveness of Behavioral Programs Presentations
Ich guidelines e9 to e12
This document provides an overview of ICH guidelines E9 through E12, which provide statistical and clinical trial design guidance. E9 discusses statistical principles for clinical trials, including trial context, scope, design techniques to avoid bias, sample size considerations, and data analysis. E10 covers choice of control groups in clinical trials and describes placebo, no treatment, dose-response, and active controls. E11 provides guidance for clinical trials in pediatric patients, including issues around timing, formulations, study types, age classifications, and ethical considerations. E12 relates to clinical evaluation by therapeutic category.
Chapter 019
This document discusses evidence-based practice and strategies for synthesizing evidence, including conducting systematic reviews and meta-analyses. It describes the 10 step process for systematic reviews, which includes formulating a clinical question, searching for and selecting studies, critically appraising studies, and developing a final report. It also discusses how to conduct meta-analyses by statistically combining data from multiple studies to determine the overall effectiveness of an intervention.
Ebm misconception myths facts
This document discusses evidence-based medicine (EBM) and addresses some common misconceptions. It outlines the benefits of EBM, including that it is a rigorous, problem-solving approach that leads to better patient outcomes when the best available evidence is incorporated into clinical decision making. Some myths are addressed, such as the idea that experience is better evidence than clinical trials, or that EBM is too time consuming. The document emphasizes that EBM helps improve quality of care when combined with clinical expertise and patient preferences.
Application of EQ-5D in Reimbursement Decision Making: The Case of NICE
This document outlines how the National Institute for Health and Care Excellence (NICE) uses cost-effectiveness analysis to inform reimbursement decisions in the UK. It discusses NICE's process and how it generally accepts interventions with an incremental cost-effectiveness ratio of less than £20,000-30,000 per quality-adjusted life year (QALY). The document emphasizes the important role of the EQ-5D questionnaire in NICE's decisions by allowing comparison of health outcomes. It addresses issues like collecting EQ-5D data, mapping from other measures, and potential limitations of EQ-5D for certain conditions.
How to establish and evaluate clinical prediction models - Statswork
A clinical prediction model can be used in various clinical contexts, including screening for asymptomatic illness, forecasting future events such as disease, and assisting doctors in their decision-making and health education. Despite the positive effects of clinical prediction models on practice, prediction modeling is a difficult process that necessitates meticulous statistical analysis and sound clinical judgments. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
Read More With Us: https://bit.ly/3dxn32c
Why Statswork?
Plagiarism Free | Unlimited Support | Prompt Turnaround Times | Subject Matter Expertise | Experienced Bio-statisticians & Statisticians | Statistics across Methodologies | Wide Range of Tools & Technologies Supports | Tutoring Services | 24/7 Email Support | Recommended by Universities
Contact Us:
Website: www.statswork.com
Email: info@statswork.com
United Kingdom: 44-1143520021
India: 91-4448137070
WhatsApp: 91-8754446690
Similar to Advanced statistical manual part i (20)
Assigning Scores For Ordered Categorical Responses
Assigning Scores For Ordered Categorical Responses
Services for Later Life: Are we any closer to integrating health and social c...
Services for Later Life: Are we any closer to integrating health and social c...
Effective Useful Life and Persistence for Behavioral Programs and Framing the...
Effective Useful Life and Persistence for Behavioral Programs and Framing the...
Application of EQ-5D in Reimbursement Decision Making: The Case of NICE
Application of EQ-5D in Reimbursement Decision Making: The Case of NICE
How to establish and evaluate clinical prediction models - Statswork
How to establish and evaluate clinical prediction models - Statswork
More from Ayurdata
Statistical distributions
This document discusses different types of statistical distributions that are found in nature. It provides examples of normal distributions that describe many biological traits like height and IQ, which tend to form a bell curve. Income distributions often follow a lognormal pattern with most people in lower income groups. Tree diameter distributions in natural forests typically take an inverse J-shape. Population age structures also form distinctive patterns over time, like a pyramid shape in the past with high child mortality rates.
BMI
This document summarizes the findings of an online survey on obesity prevalence and factors. The survey received poor response with only 53 entries. After excluding pregnant women, there were 50 observations from people in India and other countries. 62% of participants were either overweight or obese according to BMI standards. Multiple regression analysis found that age and disease condition were significantly associated with higher BMI, while disease lowered BMI. Stress, diet, and exercise habits may also contribute to the high rates of overweight and obesity seen in the sample, though larger studies are needed to verify these relationships.
Health Behaviour: An Ayurveda Perspective
This document discusses health behaviors and health education. It defines types of health behaviors like preventive, illness, and sick-role behaviors. It describes factors that influence health behaviors like lifestyle, culture, knowledge, beliefs, attitudes, values, and norms. It outlines enabling and reinforcing factors for behaviors. It discusses the aims and approaches of health education in motivating healthy behaviors and helping people develop skills to implement their health decisions. It provides tips for effective health messaging like making messages evidence-based, affordable, realistic, culturally acceptable, and meeting felt needs.
Ayur data
AyurData is celebrating its first anniversary and providing an overview of its activities in the past year. It is a group of consultants specialized in clinical trial design and analysis for Ayurvedic research. In the past year, AyurData has released basic and advanced manuals on medical statistics, provided statistical support and training to researchers, and is now tied with a US herbal firm to conduct Ayurvedic clinical trials. It is also part of an international Ayurveda research network and conducted a survey on obesity prevalence.
Ayurveda colleges and courses
The document provides information on Ayurveda colleges and courses in India as of October 2020. It lists details of several colleges, including their location, state, contact information, website, email and courses offered. Most colleges offer Bachelor of Ayurvedic Medicine and Surgery (BAMS) degrees and many also have postgraduate programs with seats ranging from 2-6 per course. The colleges are located across several states including Andhra Pradesh, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jharkhand, Karnataka, Jammu & Kashmir.
AyurData Ayurveda Webinar
AyurData intends to hold a webinar over Google Meeting Space in commemoration of its first anniversary on 7th November, 2020.
Investigation modes in ayurveda
After a long period of stagnancy since its original inception, Ayurveda research has caught up speed in the recent times. The research methodology in general got modernized both in terms of data capturing methods and inferential process. Thereby, we are witnessing more and more sophisticated study designs being employed and more of allopathic parameters being measured in investigations undertaken in Ayurveda. This article attempts to consolidate some of the methodological developments currently being pursued in the domain.
Ayurveda vs allopathy
‘Allopathy’ is an archaic terminology only used in India. The correct terminology is Modern Medicine. Modern medicine requires that all drugs are proven effective and their safety well-established before they are administered to humans
Meta-Analysis in Ayurveda
This document discusses meta-analysis and network meta-analysis in Ayurveda. It defines meta-analysis as a systematic literature review using statistical methods to aggregate findings from multiple related studies. Network meta-analysis extends this concept by including indirect treatment comparisons across different interventions studied. The document provides examples of outcomes that can be analyzed and models used. It also discusses integrating real-world evidence from non-clinical sources with randomized clinical trial data to better predict real-world results.
A manual on statistical analysis in ayurveda research
It took no time for AyurData to recognize the need for a comprehensive document describing the basic aspects of statistical applications in Ayurveda research. In fact, such a specialized publication with examples from Ayurveda was not available. So, our first attempt was to bring out one. Moreover, the content was to agree with the syllabus specified for the course on Medical Statistics for post-graduate students of Ayurveda.
A publication is now available for reference purposes both by students and other researchers working in the domain of Ayurveda for conducting experiments or surveys and also for analyzing and interpreting their results.
Classifiers
Classifiers are algorithms that map input data to categories in order to build models for predicting unknown data. There are several types of classifiers that can be used including logistic regression, decision trees, random forests, support vector machines, Naive Bayes, and neural networks. Each uses different techniques such as splitting data, averaging predictions, or maximizing margins to classify data. The best classifier depends on the problem and achieving high accuracy, sensitivity, and specificity.
Logistic regression
Logistic regression is used to model the probability of binary and multiclass classification problems. It assumes a linear relationship between predictors and the log-odds of the target variable. The regression coefficients are estimated using maximum likelihood estimation in an iterative process. Model fit is assessed using measures like deviance and likelihood ratio tests rather than R^2, with smaller deviance indicating better fit. The predictive ability of logistic regression models can be evaluated using metrics like accuracy from a confusion matrix, cross-validation, and the area under the ROC curve (AUC).
Naive bayes
Naive Bayes algorithm, in particular is a logic-based technique which is simple yet so powerful that it is often known to outperform complex algorithms for very large datasets.
More from Ayurdata (13)
A manual on statistical analysis in ayurveda research
A manual on statistical analysis in ayurveda research
Recently uploaded
Analysis insight about a Flyball dog competition team's performance
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Learn SQL from basic queries to Advance queries
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
一比一原版(UO毕业证)渥太华大学毕业证如何办理
UO毕业证录取书【微信95270640】购买（渥太华大学毕业证成绩单硕士学历）Q微信95270640代办UO学历认证留信网伪造渥太华大学学位证书精仿渥太华大学本科/硕士文凭证书补办渥太华大学 diplomaoffer,Transcript购买渥太华大学毕业证成绩单购买UO假毕业证学位证书购买伪造渥太华大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
文凭办理流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信95270640我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：渥太华大学渥太华大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信95270640）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
University of New South Wales degree offer diploma Transcript
澳洲UNSW毕业证书制作新南威尔士大学假文凭定制Q微168899991做UNSW留信网教留服认证海牙认证改UNSW成绩单GPA做UNSW假学位证假文凭高仿毕业证申请新南威尔士大学University of New South Wales degree offer diploma Transcript
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版制作【微信:41543339】【利兹贝克特大学毕业证(LeedsBeckett毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Population Growth in Bataan: The effects of population growth around rural pl...
A population analysis specific to Bataan.
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Navigating today's data landscape isn't just about managing workflows; it's about strategically propelling your business forward. Apache Airflow has stood out as the benchmark in this arena, driving data orchestration forward since its early days. As we dive into the complexities of our current data-rich environment, where the sheer volume of information and its timely, accurate processing are crucial for AI and ML applications, the role of Airflow has never been more critical.
In my journey as the Senior Engineering Director and a pivotal member of Apache Airflow's Project Management Committee (PMC), I've witnessed Airflow transform data handling, making agility and insight the norm in an ever-evolving digital space. At Astronomer, our collaboration with leading AI & ML teams worldwide has not only tested but also proven Airflow's mettle in delivering data reliably and efficiently—data that now powers not just insights but core business functions.
This session is a deep dive into the essence of Airflow's success. We'll trace its evolution from a budding project to the backbone of data orchestration it is today, constantly adapting to meet the next wave of data challenges, including those brought on by Generative AI. It's this forward-thinking adaptability that keeps Airflow at the forefront of innovation, ready for whatever comes next.
The ever-growing demands of AI and ML applications have ushered in an era where sophisticated data management isn't a luxury—it's a necessity. Airflow's innate flexibility and scalability are what makes it indispensable in managing the intricate workflows of today, especially those involving Large Language Models (LLMs).
This talk isn't just a rundown of Airflow's features; it's about harnessing these capabilities to turn your data workflows into a strategic asset. Together, we'll explore how Airflow remains at the cutting edge of data orchestration, ensuring your organization is not just keeping pace but setting the pace in a data-driven future.
Session in https://budapestdata.hu/2024/04/kaxil-naik-astronomer-io/ | https://dataml24.sessionize.com/session/667627
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
原版办【微信号:BYZS866】【兰加拉学院毕业证(Langara毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Global Situational Awareness of A.I. and where its headed
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
原版一比一多伦多大学毕业证(UofT毕业证书)如何办理
原版制作【微信:41543339】【多伦多大学毕业证(UofT毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
毕业原版【微信:176555708】【(UCSB毕业证书)圣芭芭拉分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Recently uploaded (20)
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
University of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma Transcript
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
Advanced statistical manual part i
- 1. CONFIDENTIAL © 2019 AyurData Balance Calmness Serenity Introducing Advanced Statistical Manual for Ayurveda Research Kadiroo Jayaraman Praveen Venugopal AyurData
- 2. © 2019 AyurData /CONFIDENTIAL 2 The basic manual covered the syllabus specified for M.D. students on Medical Statistics, by the Central Council of Indian Medicine. Earlier Release
- 3. © 2019 AyurData /CONFIDENTIAL 3 In the advanced manual, we have covered more advanced statistical applications including that in data science. The mode of presentation is that the concept is introduced first, followed by illustration and the use in a real context. Some mathematics will be involved but well explained in the text. Current Release
- 4. © 2019 AyurData /CONFIDENTIAL 4 TOPICS COVERED 1.Analysis of Repeated Measures 2.Multiple Linear Regression 3.Superiority, Bioequivalence and Non-inferiority trials 4.Logistic Regression 5.Decision Trees 6.Random Forest 7.Support Vector Machines 8.Naïve Bayes Classifier 9.Neural Networks 10.K-Nearest Neighbour Technique 11.Principal Component Analysis 12.Cluster Analysis 13.Stratified Multistage Sampling 14.Analysis of Time Series Data 15.Analysis of Time-to-event Data
- 5. © 2019 AyurData /CONFIDENTIAL 5 ANALYSIS OF REPEATED MEASURES Repeated measurements is a common case in Ayurveda experiments. Repeated measurements on the same individual would be correlated and so require special analysis.
- 6. © 2019 AyurData /CONFIDENTIAL 6 ANALYSIS OF REPEATED MEASURES ANOVA table for two-way with repeated measures for one factor For instance, Factor A could be treatment and B could be age group provided the patients have been stratified based on age group. In case age was a taken as a baseline variable that is continuous, it can be included as a covariate in the model. The computations and interpretations are well-explained in the manual.
- 7. © 2019 AyurData /CONFIDENTIAL 7 MULTIPLE LINEAR REGRESSION The model we are covering is, which in the matrix form would be, The model fitting, testing and residual analysis are illustrated using a real-life dataset.
- 8. © 2019 AyurData /CONFIDENTIAL 8 Superiority, Bioequivalence and Non-inferiority trials In many practical situations, we encounter the following types of comparisons: • The new drug is better than the standard drug. • The new drug is equivalent to the standard drug. • The new drug is at least as good as the standard drug. The hypothesis and test criterion to be employed in each of the above cases have to be different. For instance, Superiority hypothesis H0: ∆ = 0 H1: ∆ ≠ 0, or (∆ > 0, or ∆ <0 for one-tailed tests)
- 9. © 2019 AyurData /CONFIDENTIAL 9 Superiority, Bioequivalence and Non-inferiority trials Bio-equivalence hypothesis H0: ∆ > ∆E or ∆ < -∆E H1: ∆E ≤ ∆ ≤ ∆E where ∆E is a clinically relevant equivalence margin (usually 10%). Non-inferiority hypothesis H0: ∆ ≤-∆NI H1: ∆ >-∆NI where ∆NI is a clinically relevant non-inferiority margin (usually 10%). The tests involved and the interpretation are illustrated using examples from Ayurveda.
- 10. © 2019 AyurData /CONFIDENTIAL 10 THANK YOU © 2019 AyurData /CONFIDENTIAL 10 AyurData Team Website: http://ayurdata.in/#service-content Facebook: https://www.facebook.com/AyurData/