Soft Computing's applications is based on some biological induced methods such as genetics, development, and behavior, the warm of particles, the human nervous system, etc.
Stata is a statistical software package used widely in research, especially in economics and epidemiology. It has capabilities for data management, statistical analysis, graphics, simulations, and custom programming. Effective use of Stata involves documenting work in do-files to help with reproducibility and review processes. Graphing and modeling nonlinear relationships requires techniques like specifying quadratic terms, taking means of variables, and using commands like lowess.
Chapter 2. Multivariate Analysis of Stationary Time SeriesChengjun Wang
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This document discusses multivariate time series analysis and vector autoregressive (VAR) models. It covers simulation and estimation of VAR models in R, as well as diagnostic testing, forecasting, impulse response analysis, and structural VAR (SVAR) models which impose restrictions to identify structural shocks. Methods for SVAR models include the A-model which restricts the A matrix and the B-model which restricts the B matrix. Impulse response functions and forecast error variance decompositions are used to analyze the dynamic effects of shocks in SVAR models.
STA 506 Multivariate Analysis (MSC Statistics Class Notes) by Okoyo CollinsCollins Okoyo
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I have shared with you the summary of my class notes.
This might be important for people taking MSC Statistics courses.
The notes are for Multivariate Analysis.
This document provides an overview of multivariate analysis techniques. It defines multiple regression, discriminant analysis, MANOVA, structural equation modeling, conjoint analysis, factor analysis, cluster analysis, and multidimensional scaling. For each technique, it outlines their uses, outputs, and key concepts. The overall purpose is to help readers understand how to classify and apply different multivariate methods to analyze relationships between multiple variables and classify objects.
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The document provides instructions for launching and using the statistical software SPSS. It discusses finding the SPSS icon on the computer and launching the program. Once SPSS is open, the user can start a new data file or open an existing one. Basic steps for using SPSS are outlined, including entering data, defining variables, testing for normality, statistical analysis, and interpreting results. Specific functions and menus in SPSS are demonstrated for descriptive statistics, normality testing, and t-tests.
This document outlines a course on multivariate data analysis. It introduces key topics that will be covered, including matrix algebra, the multivariate normal distribution, principal component analysis, factor analysis, cluster analysis, discriminant analysis, and canonical correlations. The course workload consists of 40% theory and 60% practice, including a group project and weekly presentations. R will be the main software used. Examples of multivariate data and applications in various fields like business, health, and education are also provided.
Mediation, Mediation Process Mediation and Strategies For Conflict ResolutionQasim Raza
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Mediation can help parties in a dispute reach an agreement through open discussion with a neutral facilitator, rather than escalating conflict through legal action. Researchers Ellis and Jessica were having teamwork issues, and their manager recommended mediation. In individual mediation sessions, Ellis and Jessica agreed to try a joint meeting. With the mediator's guidance, they were able to openly air grievances and suggest ways to improve communication and respect boundaries going forward. This resulted in a written agreement to update behaviors and maintain open communication, with the option to involve mediators again if needed.
The document provides an overview of factor analysis, including:
- Factor analysis is a statistical technique used to reduce a large number of variables into a smaller number of underlying factors or components according to patterns of correlation between variables.
- The two main types are exploratory factor analysis, which is used when the underlying factors are unknown, and confirmatory factor analysis, which is used to test hypotheses about a predetermined factor structure.
- Key steps in factor analysis include determining the appropriateness of the data, extracting factors using various criteria, rotating factors to improve interpretation, and interpreting the results including factor loadings and communalities.
T test, independant sample, paired sample and anovaQasim Raza
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The document discusses various statistical analyses that can be performed in SPSS, including t-tests, ANOVA, and post-hoc tests. It provides details on one-sample t-tests, independent t-tests, paired t-tests, one-way ANOVA tests, and evaluating assumptions like normality. Examples are given on how to conduct these tests in SPSS and how to interpret the output. Guidance is provided on follow-up post-hoc tests that can be used after ANOVA to examine differences between specific groups.
OpenMetadata Community Meeting - 19th March 2025OpenMetadata
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The community meetup was held Wednesday March 19, 2025 @ 9:00 AM PST.
The OpenMetadata 1.7 Release Community Meeting is here! We're excited to showcase our brand-new user experience and operational workflows, especially when it comes to getting started with OpenMetadata more quickly. We also have a Community Spotlight with Gorgias, an ecommerce conversational AI platform, and how they use OpenMetadata to manage their data assets and facilitate discovery with AI.
Release 1.7 Highlights:
? Design Showcase: Brand-new UX for improved productivity for data teams
? Day 1 Experience: AI agents to auto document, tier, classify PII, & test quality
? Search Relevancy: Customizable search for more contextual, precise results
? Lineage Improvements: Scalable visualization of services, domains, & products
?? Domain Enhancements: Improved tag & glossary management across domains
? Reverse Metadata: Sync metadata back to sources for consistent governance
? Persona UI Customization: Views & workflows tailored to user responsibilities
? ¡And more!
Community Spotlight:
Antoine Balliet & Anas El Mhamdi, Senior Data Engineers from Gorgias, will share data management learnings with OpenMetadata, including data source coverage, asset discovery, and data assistance. Gorgias is the Conversational AI platform for ecommerce that drives sales and resolves support inquiries. Trusted by over 15,000 ecommerce brands, Gorgias supports growing independent shops to globally recognizable retailers.
Monthly meeting to present new and up-coming releases, discuss questions and hear from community members.
[DATAHACK SUMMIT INDIA 2019] Federated Learning using Deep LearningTuhinSharma15
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Federated learning is a family of Machine Learning algorithms that has the core idea: a connected network exists in which there is a central server node. Each of the nodes creates data ¨C that has to be used for training as well as for prediction. Each of the nodes trains a local model and only that model is shared with the server, not the data. In this talk, We talk about how to build deep learning models using federated learning that is truly privacy-preserving. We will show how to build custom algorithms and loss functions.
Key Takeaways:
Introduction to Federated Learning
Decentralized Training
Encryption
Differential Privacy
Federated Learning ¨C Notebook
Introduction
Custom algorithm and loss function
Interior Design of Brihadisvara Temple.pptxJyotikaNegi
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One of the largest temples in India, the Brihadeeswara One of the largest temples in India, the Brihadeeswara Temple also known as Peruvudaiyar Kovil is located in Thanjavur. Dedicate to Lord Shiva represented as a huge ¡®Lingam¡¯, the temple was built around 1010 AD by the Chola king Rajaraja Chola I. Considered as one of the three ¡®Great Living Chola Temples¡¯ along with the Gangaikondacholeeswaram Temple and Airavastesvara Temple, the complex is also listed as a part of the UNESCO World Heritage Sites.
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¡°Unlocking GrowthThe Power of Digital Marketing in 2025.pdfpsvimal758
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Digital marketing refers to the use of online platforms, digital channels, and technologies to promote products, services, or brands to a targeted audience. It encompasses various strategies such as search engine optimization (SEO), social media marketing, email marketing, content marketing, pay-per-click (PPC) advertising, and influencer marketing. Digital marketing enables businesses to reach potential customers globally, engage with audiences in real-time, and track performance through data analytics. Its goal is to drive brand awareness, generate leads, increase sales, and build long-term customer relationships through digital means.
This document provides an overview of multivariate analysis techniques. It defines multiple regression, discriminant analysis, MANOVA, structural equation modeling, conjoint analysis, factor analysis, cluster analysis, and multidimensional scaling. For each technique, it outlines their uses, outputs, and key concepts. The overall purpose is to help readers understand how to classify and apply different multivariate methods to analyze relationships between multiple variables and classify objects.
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The document provides instructions for launching and using the statistical software SPSS. It discusses finding the SPSS icon on the computer and launching the program. Once SPSS is open, the user can start a new data file or open an existing one. Basic steps for using SPSS are outlined, including entering data, defining variables, testing for normality, statistical analysis, and interpreting results. Specific functions and menus in SPSS are demonstrated for descriptive statistics, normality testing, and t-tests.
This document outlines a course on multivariate data analysis. It introduces key topics that will be covered, including matrix algebra, the multivariate normal distribution, principal component analysis, factor analysis, cluster analysis, discriminant analysis, and canonical correlations. The course workload consists of 40% theory and 60% practice, including a group project and weekly presentations. R will be the main software used. Examples of multivariate data and applications in various fields like business, health, and education are also provided.
Mediation, Mediation Process Mediation and Strategies For Conflict ResolutionQasim Raza
?
Mediation can help parties in a dispute reach an agreement through open discussion with a neutral facilitator, rather than escalating conflict through legal action. Researchers Ellis and Jessica were having teamwork issues, and their manager recommended mediation. In individual mediation sessions, Ellis and Jessica agreed to try a joint meeting. With the mediator's guidance, they were able to openly air grievances and suggest ways to improve communication and respect boundaries going forward. This resulted in a written agreement to update behaviors and maintain open communication, with the option to involve mediators again if needed.
The document provides an overview of factor analysis, including:
- Factor analysis is a statistical technique used to reduce a large number of variables into a smaller number of underlying factors or components according to patterns of correlation between variables.
- The two main types are exploratory factor analysis, which is used when the underlying factors are unknown, and confirmatory factor analysis, which is used to test hypotheses about a predetermined factor structure.
- Key steps in factor analysis include determining the appropriateness of the data, extracting factors using various criteria, rotating factors to improve interpretation, and interpreting the results including factor loadings and communalities.
T test, independant sample, paired sample and anovaQasim Raza
?
The document discusses various statistical analyses that can be performed in SPSS, including t-tests, ANOVA, and post-hoc tests. It provides details on one-sample t-tests, independent t-tests, paired t-tests, one-way ANOVA tests, and evaluating assumptions like normality. Examples are given on how to conduct these tests in SPSS and how to interpret the output. Guidance is provided on follow-up post-hoc tests that can be used after ANOVA to examine differences between specific groups.
OpenMetadata Community Meeting - 19th March 2025OpenMetadata
?
The community meetup was held Wednesday March 19, 2025 @ 9:00 AM PST.
The OpenMetadata 1.7 Release Community Meeting is here! We're excited to showcase our brand-new user experience and operational workflows, especially when it comes to getting started with OpenMetadata more quickly. We also have a Community Spotlight with Gorgias, an ecommerce conversational AI platform, and how they use OpenMetadata to manage their data assets and facilitate discovery with AI.
Release 1.7 Highlights:
? Design Showcase: Brand-new UX for improved productivity for data teams
? Day 1 Experience: AI agents to auto document, tier, classify PII, & test quality
? Search Relevancy: Customizable search for more contextual, precise results
? Lineage Improvements: Scalable visualization of services, domains, & products
?? Domain Enhancements: Improved tag & glossary management across domains
? Reverse Metadata: Sync metadata back to sources for consistent governance
? Persona UI Customization: Views & workflows tailored to user responsibilities
? ¡And more!
Community Spotlight:
Antoine Balliet & Anas El Mhamdi, Senior Data Engineers from Gorgias, will share data management learnings with OpenMetadata, including data source coverage, asset discovery, and data assistance. Gorgias is the Conversational AI platform for ecommerce that drives sales and resolves support inquiries. Trusted by over 15,000 ecommerce brands, Gorgias supports growing independent shops to globally recognizable retailers.
Monthly meeting to present new and up-coming releases, discuss questions and hear from community members.
[DATAHACK SUMMIT INDIA 2019] Federated Learning using Deep LearningTuhinSharma15
?
Federated learning is a family of Machine Learning algorithms that has the core idea: a connected network exists in which there is a central server node. Each of the nodes creates data ¨C that has to be used for training as well as for prediction. Each of the nodes trains a local model and only that model is shared with the server, not the data. In this talk, We talk about how to build deep learning models using federated learning that is truly privacy-preserving. We will show how to build custom algorithms and loss functions.
Key Takeaways:
Introduction to Federated Learning
Decentralized Training
Encryption
Differential Privacy
Federated Learning ¨C Notebook
Introduction
Custom algorithm and loss function
Interior Design of Brihadisvara Temple.pptxJyotikaNegi
?
One of the largest temples in India, the Brihadeeswara One of the largest temples in India, the Brihadeeswara Temple also known as Peruvudaiyar Kovil is located in Thanjavur. Dedicate to Lord Shiva represented as a huge ¡®Lingam¡¯, the temple was built around 1010 AD by the Chola king Rajaraja Chola I. Considered as one of the three ¡®Great Living Chola Temples¡¯ along with the Gangaikondacholeeswaram Temple and Airavastesvara Temple, the complex is also listed as a part of the UNESCO World Heritage Sites.
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¡°Unlocking GrowthThe Power of Digital Marketing in 2025.pdfpsvimal758
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Digital marketing refers to the use of online platforms, digital channels, and technologies to promote products, services, or brands to a targeted audience. It encompasses various strategies such as search engine optimization (SEO), social media marketing, email marketing, content marketing, pay-per-click (PPC) advertising, and influencer marketing. Digital marketing enables businesses to reach potential customers globally, engage with audiences in real-time, and track performance through data analytics. Its goal is to drive brand awareness, generate leads, increase sales, and build long-term customer relationships through digital means.
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CHATGPT PROMPTS _ AI Prompts for Lead Generation Analysis (1).pdfAbrar Sohail
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AI chatbots are transforming how growth teams approach lead generation by bringing human-centric analysis to data-driven marketing. These intelligent tools leverage natural language processing to convert raw campaign data into actionable insights, helping professionals refine their strategies with precision.
Data Transformation: Convert raw campaign data into clear, actionable insights.
Precision Optimization: Refine marketing strategies with granular, data-backed recommendations.
Time Efficiency: Automate complex data analysis, freeing up time for strategic thinking
Collaboration Enhancement: Create shareable reports that align teams and stakeholders.
Trend Identification: Detect shifts in conversion rates, cost per lead, and lead quality over time.
Performance Benchmarking: Compare your lead generation metrics against industry standards.
Channel Optimization: Identify underperforming channels and demographic targeting gaps.
Solution Recommendations: Suggest specific improvements like A/B testing or messaging adjustments.
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Historical Data Analysis: Upload past campaign data to establish performance baselines.
Specific Query Formulation: Structure questions clearly to get targeted, useful responses.
Iterative Refinement: Use follow-up questions to drill deeper into specific insights
Human-AI Collaboration: Combine AI insights with your team's expertise for optimal decision-making.
By integrating AI chatbots into their workflow, growth professionals can act faster on data insights while focusing their expertise on high-impact tasks. This human-machine collaboration represents the future of sophisticated, efficient lead generation strategies that drive measurable business results.
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Statistician
1. Profile Summary
Mr. Collins Omondi Okoyo is a Statistician, with close to two years experience in statistical data analysis and management. He has special interest in survey data analysis, longitudinal/ panel data analysis, cross ¨C sectional data analysis, multilevel data, survival data analysis and Geostatstical/ Geospatial analysis using ArcGIS for Desktop. He programs and implements mobile data collection system especially Open Data Kit (ODK). He is presently the Project Data manager at Kenya Medical Research Institute (KEMRI), Eastern and Southern Africa Centre of International Parasite Control (ESACIPAC).