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http://email.fdc-k.ngo/tracking/click?d=Igc_mk9-YF1Xi-sKmLzoETPspB6EZyE9HrHaWRKJ4HMXRI9MfzblTHE1NDcGOl__4zFTeXzT2ov9UHvD6evX2Y7t6NWrgKtKjOhrOTHA2mD0s-NSnrL4UQlqzURvmkg7tpmYDZ26GYvky1QMUa5fYvr_0WAGKo2HNbBvoFhw1wMa0 Download our Calender 2022 ·         FOSCORE DEVELOPMENT CENTER http://email.fdc-k.ngo/tracking/click?d=yic_nxDoLAWK-PAnm7nPI2g-UVYf8xAYH0q2uxXwLg839IzuvNjaysUqlKC_peNYxUm3Hsscho0zAraKrBjpGMYHeXj22yjdSWFpmGgVGiaVXP-9chCelt5B_WZjjJYEY5JIMBuPc9ggOIgwYBrxFMLaRsuB4zI57bBJLR_Ou6-3Uf1FPSnmYrYAR9f4fwPpoA2 www.fdc-k.org   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?  How can organizations go beyond merely generating new insights to changing behaviors — not only of their employees, but beneficiary and communities too? 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 SPSS 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 ·         Perform basic data analysis tasks with SPSS ·         Perform simple to complex data management tasks using SPSS ·         Correctly identify appropriate statistical test for basic analysis s and perform them using SPSS ·         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: o    ODK Build o    Koboforms o    PurcForms ·         Hands-on Exercise Module 6:Preparing the mobile phone for data collection ·         Installing applications: ODK Collect o    Using Google play o    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 o    Required questions o    Constraining responses o    Skip: Asking Relevant questions o    The specify other ·         Grouping questions o    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 charts ·         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: Introduction to SPSS   ·         What is SPSS? ·         Opening SPSS ·         Layout of SPSS ·         Exiting SPSS ·         Exercises ·         Brief description and history of SPSS Module 27: Overview of SPSS ·         The Title Bar ·         The Menu Bar ·         The (Power) Tool Bar ·         The Data Editor (Data View and Variable view) ·         The Status Bar Module 28: Entering Data   ·         The Logic of Data Files ·         Entering Data ·         Inserting a Variable ·         Inserting a Case ·         Merging Files ·         Reading Data From Other Sources  Module 29: Graphing Data   ·         Frequency Distributions ·         Histograms ·         Stem-and-Leaf Plot ·         Boxplots ·         Bar Graphs ·         Line Graphs ·         Scatterplots ·         Pie Charts C ·         hart Templates ·         Exercises Module 30: Descriptive Statistics: Measures of Variability and Central Tendency   ·         Descriptive Statistics ·         Frequencies ·         Crosstabs ·         Compare Means ·         Exercise Module 31: Correlation   ·         Correlation ·         Subgroup Correlations ·         Scatterplots of Data by Subgroups ·         Overlay Scatterplots ·         Exercises  Module 32: Regression and Multiple Regression ·         Regression ·         Multiple Regression ·         Exercises  Module 33: Comparing Means Using t-tests  ·         One Sample t-tests ·         Paired Sample t-tests ·         Independent Samples t-tests ·         Exercises Module 34: Comparing Means Using One-Way ANOVA  ·         One-Way Anova ·         General Linear Model to Calculate One-Way ANOVAs ·         Exercises  Module 35: Comparing Means Using Factorial ANOVA  ·         Factorial ANOVA Using GLM Univariate ·         Simple Effects ·         Exercises  Module 36: Comparing Means Using Repeated Measures ANOVA  ·         Using GLM Repeated Measures to Calculate Repeated Measures ANOVAs ·         Multiple Comparisons ·         Exercises  Module 37:Chi-Square  ·         Goodness of Fit Chi Square All Categories Equal ·         Goodness of Fit Chi Square Categories Unequal ·         Chi Square for Contingency Tables ·         Exercises  Module 38: Nonparametric Statistics  ·         Mann-Whitney Test ·         Wilcoxon’s Matched Pairs Signed-Ranks Test ·         Kruskal-Wallis One-Way ANOVA ·         Friedman’s Rank Test for k Related Samples ·         Exercises Module 39: 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 ·         Exercise:Preparing a report for the survey, a communication and dissemination plan and a demand and use strategy. ·         Presentations and joint action planning   General Notes ·         All our courses can be Tailor-made to participants' needs ·         The participant must be conversant in English ·         Presentations are well-guided, practical exercises, web-based tutorials, and group work. Our facilitators are experts with more than 10 years of experience. ·         Upon completion of training the participant will be issued with a Foscore development center certificate (FDC-K) ·         Training will be done at the Foscore development center (FDC-K) centers. We also offer inhouse and online training on the client schedule ·         Course duration is flexible and the contents can be modified to fit any number of days. ·         The course fee for onsite training includes facilitation training materials, 2 coffee breaks, a buffet lunch, and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance, and other personal expenses. ·         Accommodation, pickup, freight booking, and Visa processing arrangement, are done on request, at discounted prices. ·         Tablet and Laptops are provided to participants on request as an add-on cost to the training fee. ·         One-year free Consultation and Coaching provided after the course. ·         Register as a group of more than two and enjoy a discount of (10% to 50%) ·         Payment should be done before commence of the training or as agreed by the parties, to the FOSCORE DEVELOPMENT CENTER account, so as to enable us to prepare better for you. ·         For any inquiries reach us at training@fdc-k.org or +254712260031    ·         Website: http://email.fdc-k.ngo/tracking/click?d=9i8NH0YxugT77q2FrIW15Vo0NK3XStLCZWGP4h8yMfHp-q2ydDtWeDJq8eJYVFHHIFpYUewdHdLlnN55uBqdh4bblEnSxPuOQbr4n9XKPdQleMFhqOsYyMTJyvDDWbo4Ow2 www.fdc-k.org   Indicative Budget The registration cost is indicated in every course for online and onsite trainings find the group rate discount below:

Group Size Discount Rate for Group 2-7 20% 8-21 25% 22-31 30% 32-41 35% 42-51 40% 52> Above 50% Other Important Links ·

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