Invitation to Research Design,ODK mobile data collection,GIS data mapping,Data analysis using NVIVO and R training

[FDC Training]

Title: Invitation to Research Design,ODK mobile data collection,GIS data mapping,Data analysis using NVIVO and R training

Research Design, mobile data collection and mapping and Data analysis using NVIVO and R course-Nov 09 to Nov 20,2020 for 10Days Register for online Training's or normal training and upcoming trainings on the same Download PDF Calendar Foscore Development Center  INTRODUCTION New developments in data science offer a tremendous opportunity to improve decision-making. In the development world, there has been an increase in the number of data gathering initiative such as baseline surveys, Socio-Economic Surveys, Demographic and Health Surveys, Nutrition Surveys, Food Security Surveys, Program Evaluation Surveys, Employees, customers and vendor satisfaction surveys, and opinion polls among others, all intended to provide data for decision making. It is essential that these efforts go beyond merely generating new insights from data but also to systematically enhance individual human judgment in real development contexts. How can organizations better manage the process of converting the potential of data science to real development outcomes This ten days hands-on course is tailored to put all these important consideration into perspective. It is envisioned that upon completion, the participants will be empowered with the necessary skills to produce accurate and cost effective data and reports that are useful and friendly for decision making. It will be conducted using ODK, GIS, NVIVO and R DURATION 2 Weeks LEARNING OBJECTIVES Understand and appropriately use statistical terms and concepts Design and Implement universally acceptable Surveys Convert data into various formats using appropriate software Use mobile data gathering tools such as Open Data Kit (ODK) Use GIS software to plot and display data on basic maps Qualitative data analysis using NVIVO Analyze t data by applying appropriate statistical techniques using R Interpret the  statistical analysis using R Identify statistical techniques a best suited to data and questions Strong foundation in fundamental statistical concepts Implement different statistical analysis in R and interpret the results Build intuitive data visualizations Carry out formalized hypothesis testing Implement linear modelling techniques such multiple regressions and GLMs Implement advanced regression analysis and multivariate analysis Write reports from survey data Put strategies to improve data demand and use in decision making WHO SHOULD ATTEND? This is a general course targeting participants with elementary knowledge of Statistics from Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Medical or public health professionals among others who already have some statistical knowledge, but wish to be conversant with the concepts and applications of statistical modeling. TOPICS TO BE COVERED Module1: Basic statistical terms and concepts Introduction to statistical concepts Descriptive Statistics Inferential statistics Module 2:Research Design The role and purpose of research design Types of research designs The research process Which method to choose? Exercise: Identify a project of choice and developing a research design Module 3: Survey Planning, Implementation and Completion Types of surveys The survey process Survey design Methods of survey sampling Determining the Sample size Planning a survey Conducting the survey After the survey Exercise: Planning for a survey based on the research design selected Module 4:Introduction Introduction to Mobile Data gathering Benefits of Mobile Applications Data and types of Data Introduction to common mobile based data collection platforms Managing devices Challenges of Data Collection Data aggregation, storage and dissemination Types of questions Data types for each question Types of questionnaire or Form logic Extended data types geoid, image and multimedia Module 5:Survey Authoring Design forms using a web interface using: ODK Build Koboforms PurcForms Hands-on Exercise Module 6:Preparing the mobile phone for data collection Installing applications: ODK Collect Using Google play Manual install (.apk files) Configuring the device (Mobile Phones) Uploading the form into the mobile devices Hands-on Exercise Module 7:Designing forms manually: Using XLS Forms Introduction to XLS forms syntax New data types Notes and dates Multiple choice Questions Multiple Language Support Hints and Metadata Hands-on Exercise Module 8:Advanced survey Authoring Conditional Survey Branching Required questions Constraining responses Skip: Asking Relevant questions The specify other Grouping questions Skipping many questions at once (Skipping a section) Repeating a set of questions Special formatting Making dynamic calculations Module 9:Hosting survey data (Online) ODK Aggregate Formhub ona.io KoboToolbox Uploading forms to the server Module 10:Hosting Survey Data (Configuring a local server) Configuring ODK Aggregate on a local server Downloading data Manual download (ODK Briefcase) Using the online server interface Module 11: GIS mapping of survey data using QGIS Introduction to GIS for Researchers and data scientists Importing survey data into a GIS Mapping of survey data using QGIS Exercise: QGIS mapping exercise. Module 12:Understanding Qualitative Research Qualitative Data Types of Qualitative Data Sources of Qualitative data Qualitative vs Quantitative NVivo key terms The NVivo Workspace Module 13:Preliminaries of Qualitative data Analysis What is qualitative data analysis Approaches in Qualitative data analysis; deductive and inductive approach Points of focus in analysis of text data Principles of Qualitative data analysis Process of Qualitative data analysis Module 14:Introduction to NVIVO NVIVO Key terms NVIVO interface NVIVO workspace Use of NVIVO ribbons Module 15:NVIVO Projects Creating new projects Creating a new project Opening and Saving project Working with Qualitative data files Importing Documents Merging and exporting projects Managing projects Working with different data sources Module 16:Nodes in NVIVO Theme codes Case nodes Relationships nodes Node matrices Type of Nodes, Creating nodes Browsing Nodes Creating Memos Memos, annotations and links Creating a linked memo Module 17:Classes and summaries Source classifications Case classifications Node classifications Creating Attributes within NVivo Importing Attributes from a Spreadsheet Getting Results; Coding Query and Matrix Query Module 18: Coding Data-driven vs theory-driven coding Analytic coding Descriptive coding Thematic coding Tree coding Module 19:Thematic Analytics in NVIVO Organize, store and retrieve data Cluster sources based on the words they contain Text searches and word counts through word frequency queries. Examine themes and structure in your content Module 20:Queries using NVIVO Queries for textual analysis Queries for exploring coding Module 21: Building on the Analysis Content Analysis; Descriptive, interpretative Narrative Analysis Discourse Analysis Grounded Theory Module 22: Qualitative Analysis Results Interpretation Comparing analysis results with research questions Summarizing finding under major categories Drawing conclusions and lessons learned Module 23: Visualizing NVIVO project Display data in charts0 Creating models and graphs to visualize connections Tree maps and cluster analysis diagrams Display your data in charts Create models and graphs to visualize connections Create reports and extracts Module 24: Triangulating results and Sources Triangulating with quantitative data Using different participatory techniques to measure the same indicator Comparing analysis from different data sources Checking the consistency on respondent on similar topic Module 25: Report Writing Qualitative report format Reporting qualitative research Reporting content Interpretation MODULE 26:Basics of Applied Statistical Modelling using R Introduction to the Instructor and Course Data & Code Used in the Course Statistics in the Real World Designing Studies & Collecting Good Quality Data Different Types of Data MODULE 27: Essentials of the R Programming  Rationale for this section Introduction to the R Statistical Software & R Studio Different Data Structures in R Reading in Data from Different Sources Indexing and Subletting of Data Data Cleaning: Removing Missing Values Exploratory Data Analysis in R MODULE 28: Statistical Tools  Quantitative Data Measures of Center Measures of Variation Charting & Graphing Continuous Data Charting & Graphing Discrete Data Deriving Insights from Qualitative/Nominal Data MODULE 29: Probability Distributions Data Distribution: Normal Distribution Checking For Normal Distribution Standard Normal Distribution and Z-scores Confidence Interval-Theory Confidence Interval-Computation in R MODULE 30: Statistical Inference  Hypothesis Testing T-tests: Application in R Non-Parametric Alternatives to T-Tests One-way ANOVA Non-parametric version of One-way ANOVA Two-way ANOVA Power Test for Detecting Effect MODULE 31: Relationship between Two Different Quantitative Variables Explore the Relationship Between Two Quantitative Variables Correlation Linear Regression-Theory Linear Regression-Implementation in R Conditions of Linear Regression Multi-collinearity Linear Regression and ANOVA Linear Regression With Categorical Variables and Interaction Terms Analysis of Covariance (ANCOVA) Selecting the Most Suitable Regression Model Violation of Linear Regression Conditions: Transform Variables Other Regression Techniques When Conditions of OLS Are Not Met Regression: Standardized Major Axis (SMA) Regression Polynomial and Non-linear regression Linear Mixed Effect Models Generalized Regression Model (GLM) Logistic Regression in R Poisson Regression in R Goodness of fit testing MODULE 32: Multivariate Analysis Introduction Multivariate Analysis Cluster Analysis/Unsupervised Learning Principal Component Analysis (PCA) Linear Discriminant Analysis (LDA) Correspondence Analysis Similarity & Dissimilarity Across Sites Non-metric multi-dimensional scaling (NMDS) Multivariate Analysis of Variance (MANOVA) Module 33: Report writing for surveys, data dissemination, demand and use Writing a report from survey data Communication and dissemination strategy Context of Decision Making Improving data use in decision making Culture Change and Change Management Preparing a report for the survey, a communication and dissemination plan and a demand and use strategy. Presentations and joint action planning READMORE Foscore Development Centre (FDC-K) Foscore Development Center Kenya (FDC-K) is a global training and consulting firm that has been assisting organizations and individuals to achieve their objectives and goals. We specialize in monitoring and evaluation, impact assessment of institutional, human capacity development needs assessment, strategy development, investment planning, implementation and talent development solutions for individuals and organizations, through our highly customized program delivery courses. We have experienced expert teams in a wide array of disciplines to meet the requirements of our clients and investors. The FDC-K is dedicated to delivering holistic workplace professional, vocational, educational and capacity development solutions aimed at bettering the performance of individuals and groups within the organizations. We also do capacity development solutions through training, software development and sales, among others. The services offered by the FDC-K Consultancy Unit are divided into three (3) broad categories, namely: Service Consultancy, Contract Research, Training and Capacity Building described as follows: 1. Service Consultancy: FDC-K provides expert professional advice in specific areas identified by the client based on client requirements and specifications. Some services in this area include management and business advisory services, information technology services, risk management and advisory services, enterprise risk management services, standardization and compliance services, strategic planning services, among others. We apply these services towards the capacity development programs, as shown below. 2. Contract Research: These are services which revolve around research-based consultancy services which leads to the generation of new knowledge, synthesis and analysis of existing knowledge to formulate new creative concepts, innovations, designs, methodologies, understandings, applications and solutions for specified problems on mutually agreed terms and conditions. Services in this category include monitoring and evaluation services, tracer studies, baseline surveys, training needs assessments, customer and employee satisfaction, work environment assessments, development programs, impact ’assessments’ studies and market survey. We bring these research skills to bear on the capacity needs assessment, strategy development and investment planning as described in this proposal. 3. Training and Capacity Development: FDC-K provides tailor-made in-service courses, lasting from a few days to several weeks. The training is aimed at improving knowledge, skills and competence that results in better performance and high professional productivity. Courses offered are delivered by qualified professionals from relevant disciplines and specializations. This experience has given FDC-K a unique advantage as we see the capacity gaps among the professional and develop strategies to fill them regularly. We bring this expertise to addressing issues facing the institutional capacity development plans as needed by this proposal.  FDC IMPORTANT LINKS ONLINE TRAINING'S NORMAL ATTENDANCE TRAINING'S TRAINING,S PHOTOS CONTACT US Contact our training team directly via Whats-app  DOWNLOAD OUR COURSE CALENDAR DOWNLOAD OUR BROCHURE Call +254712260031 OR EMAIL: train...@fdc-k.org Visit our Website For More Information RESEARCH AND DATA ANALYSIS TRAINING'S HUMANITARIAN TRAINING'S MONITORING AND EVALUATION TRAINING'S RESEARCH AND DATA ANALYSIS TRAINING'S TECHNOLOGY TRAINING'S AGRICULTURE TRAINING'S GIS MAPPING TRAINING'S GOVERNANCE TRAINING'S CONSULTANCY OUR ONLINE TRAINING PROCEDURE Select course of your preference Register online as individual, online training or group and you will automatically receive invoice and invitation letter to enable your attendance. Online Training classes are instructor-led, live online training you attend from your home or work or in one of our local computer labs. Our live online instructors teach you from a remote location while being able to interact with other participants as in a traditional training setting.This will include: A real, live instructor teaching you from another location Hands-on learning with the software/skills you are being taught Interaction with all students in the class at other locations Any needed software for class provided in online lab environment Easy assistance from the instructor Looking forward to your registration and attendance.Result Based skills Development Regards, FDC Training Team Telephone office: +254712260031 Email train...@fdc-k.org Contact our training team directly via WhatsApp You can opt out of future communications about our services by clicking on the unsubscribe link below.Thank you If you'd like to unsubscribe and stop receiving these emails click here.