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dmarc=none header.from=fdc-k.or.ke; arc=none Received: from o50316380.outbound-mail.sendgrid.net ([50.31.63.80]:25814) by zero.zsh.org with esmtps (TLS1.3:TLS_AES_128_GCM_SHA256:128) id 1m0k9X-000BQe-8u; Tue, 06 Jul 2021 12:26:16 +0000 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=fdc-k.or.ke; h=content-transfer-encoding:content-type:from:mime-version:subject:to: list-unsubscribe; s=s1; bh=dFgop2qr1OC7XZ9bVt3P7wLnQlS+7po7O9NP4tFsSwk=; b=XTlX2iNi80tikhplNmLcUmBUbjjc9lzx42YrrysccQnA0b/NFdtlsfWeJHtWF4zHHiP0 JHxw89oM6deQUdIMR0W90s+sNc8EThJhkkikNGQeK7tEcpiOS6haxwpoicXw9vSQP/h2Y3 YpjlPBxSdXmWV01O97xe0Kf0EGmnputSk= Received: by filterdrecv-76c84c4896-tvjs5 with SMTP id filterdrecv-76c84c4896-tvjs5-1-60E44BCC-AD 2021-07-06 12:25:49.65808436 +0000 UTC m=+488583.303275230 Received: from MTc0MzAzNDc (unknown) by geopod-ismtpd-1-1 (SG) with HTTP id db8VvO5YSneMeHLG4_GGZA Tue, 06 Jul 2021 12:25:48.450 +0000 (UTC) Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset=iso-8859-1 Date: Tue, 06 Jul 2021 12:26:12 +0000 (UTC) From: FDC -K Mime-Version: 1.0 Message-ID: Subject: Invitation to Research Design,ODK,GIS,NVIVO and R Worksop Workshop X-SG-EID: =?us-ascii?Q?FmYxzXHSc487tbDm1wrJZjg=2FcsgLXQD6zWf6qas=2F2yid9uvgS94Wjs6+XdrERt?= =?us-ascii?Q?aKaQizotuMmR4DC2MNGbJSBC6UEIgNR0M8LM6IV?= =?us-ascii?Q?sKYW6cbmPyepXT6fUn66ns5FV3CwW5TE11ufZsC?= =?us-ascii?Q?6Ho1EyEcgLidNWFYh2Ea85OD6xhq3bXuaDb6gR7?= =?us-ascii?Q?N9SYb9I1xkowWd9D+FN7o72NCIwBhUkR4xxBgsx?= =?us-ascii?Q?mERAAJFpE9tmbX5rRfEV7O7YaqXjAVNfa8MAGi?= To: zsh-workers@zsh.org X-Entity-ID: lgZohGoWIjvYsKzlUpYsxA== List-Unsubscribe: =?us-ascii?Q?=3Cmailto=3Aunsubscribe=40em9210=2Efdc-k=2Eor=2Eke=3Fsubject=3Dhttp=3A=2F=2Furl9271=2E?= =?us-ascii?Q?fdc-k=2Eor=2Eke=2Fwf=2Funsubscribe*q*upn=3DoyPD-2?= =?us-ascii?Q?Bi0SoJcalg3AUqBThp5JaR2grl-2Fx1rud8s8VI?= =?us-ascii?Q?GFVYhXTbj4aDqqXcsZ-2FCnucitERmwQ8vnEGCj?= =?us-ascii?Q?VRlRmDAkAPerSQYVfJ1mYWy9Ixa0oDq7vyTbK4s?= =?us-ascii?Q?UUVr14RVKel7AOxSKhgHps8M-2BAyeBVWQXOG4E?= =?us-ascii?Q?ELy2B18t9zNDMUZ5IB9LP7Jpwlc6w5tjOwqrUGn?= =?us-ascii?Q?brF6sTjVyrXgNwQBsYkAznGMI9Ps6qUibgjeT4Y?= =?us-ascii?Q?RIE-3D=3E?= X-Seq: 49148 Archived-At: X-Loop: zsh-workers@zsh.org Errors-To: zsh-workers-owner@zsh.org Precedence: list Precedence: bulk Sender: zsh-workers-request@zsh.org X-no-archive: yes List-Id: List-Help: List-Subscribe: List-Unsubscribe: List-Post: List-Owner: List-Archive: Invitation to Research Design,ODK,GIS,NVIVO and R Worksop Wo= rkshop

Research Design,ODK mobi= le data collection,GIS data mapping,Data analysis using NVIVO and R Worksho= ps-July 26 to August 06,2021 for 10 Days

<= tbody>
=A0Register for= online attendance Workshop

Register Onsite attendance workshop

=A0Register as a group workshop

Download PD= F Calendar 2021 Workshops
=A0
Onsite Centers: Hilton = Hotel, Prideinn and Meridian Hotel,Kenya
<= br />
OFFICIAL EMAIL ADDRESS: training@fdc-k.org

Office Tel= ephone: +254712260031

INTRODUCT= ION
New developments in data science offer a tremendous oppor= tunity to improve decision-making. In the development world, there has been= an increase in the number of data gathering initiative such as baseline su= rveys, Socio-Economic Surveys, Demographic and Health Surveys, Nutrition Su= rveys, Food Security Surveys, Program Evaluation Surveys, Employees, custom= ers and vendor satisfaction surveys, and opinion polls among others, all in= tended to provide data for decision making.
It is essential that these= efforts go beyond merely generating new insights from data but also to sys= tematically enhance individual human judgment in real development contexts.= How can organizations better manage the process of converting the potentia= l of data science to real development outcomes This ten days hands-on cours= e is tailored to put all these important consideration into perspective. It= is envisioned that upon completion, the participants will be empowered wit= h the necessary skills to produce accurate and cost effective data and repo= rts that are useful and friendly for decision making.
It will be condu= cted using ODK, GIS, NVIVO and R
DURATION
2 Week= s
LEARNING OBJECTIVES
  • Understand= and appropriately use statistical terms and concepts
  • Design and Im= plement universally acceptable Surveys
  • Convert data into various fo= rmats using appropriate software
  • Use mobile data gathering tools su= ch as Open Data Kit (ODK)
  • Use GIS software to plot and display data= on basic maps
  • Qualitative data analysis using NVIVO
  • Analyz= e t data by applying appropriate statistical techniques using R
  • Int= erpret the statistical analysis using R
  • Identify statistical techni= ques a best suited to data and questions
  • Strong foundation in funda= mental statistical concepts
  • Implement different statistical analysi= s in R and interpret the results
  • Build intuitive data visualization= s
  • Carry out formalized hypothesis testing
  • Implement linear = modelling techniques such multiple regressions and GLMs
  • Implement a= dvanced 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 Statist= ics 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 concept= s and applications of statistical modeling.
TOPICS TO BE COVER= ED
Module1: Basic statistical terms and concepts
  • Introduction to statistical concepts
  • Desc= riptive Statistics
  • Inferential statistics
Module 2= :Research Design
  • The role and purpose of rese= arch design
  • Types of research designs
  • The research process<= /li>
  • Which method to choose?
  • Exercise: Identify a project of cho= ice and developing a research design
Module 3: Survey Plan= ning, Implementation and Completion
  • Types of = surveys
  • The survey process
  • Survey design
  • Methods of= survey sampling
  • Determining the Sample size
  • Planning a sur= vey
  • Conducting the survey
  • After the survey
  • Exercise= : Planning for a survey based on the research design selected
Module 4:Introduction
  • Introduction to Mob= ile 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 question= s
  • Data types for each question
  • Types of questionnaire or Fo= rm logic
  • Extended data types geoid, image and multimedia
<= strong>Module 5:Survey Authoring
  • Design forms= using a web interface using:
  • ODK Build
  • Koboforms
  • P= urcForms
  • Hands-on Exercise
Module 6:Preparing the = mobile phone for data collection
  • Installing a= pplications: ODK Collect
  • Using Google play
  • Manual install (= .apk files)
  • Configuring the device (Mobile Phones)
  • Uploadin= g 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
  • No= tes and dates
  • Multiple choice Questions
  • Multiple Language S= upport
  • Hints and Metadata
  • Hands-on Exercise
Module 8:Advanced survey Authoring
  • Conditio= nal Survey Branching
  • Required questions
  • Constraining respon= ses
  • Skip: Asking Relevant questions
  • The specify other
    • <= li>Grouping questions
  • Skipping many questions at once (Skipping a s= ection)
  • Repeating a set of questions
  • Special formatting
  • Making dynamic calculations
Module 9:Hosting survey d= ata (Online)
  • ODK Aggregate
  • Formhub
  • ona.io
  • KoboToolbox
  • Uploading forms to the server
    • =
  • Module 10:Hosting Survey Data (Configuring a local server)
  • Conf= iguring ODK Aggregate on a local server
  • Downloading data
  • Ma= nual 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 usin= g QGIS
  • Exercise: QGIS mapping exercise.
Module 12:= Understanding Qualitative Research
  • Qualitativ= e Data
  • Types of Qualitative Data
  • Sources of Qualitative dat= a
  • Qualitative vs Quantitative
  • NVivo key terms
  • The N= Vivo Workspace
Module 13:Preliminaries of Qualitative data= Analysis
  • What is qualitative data analysis
  • Approaches in Qualitative data analysis; deductive and inductive app= roach
  • Points of focus in analysis of text data
  • Principles o= f Qualitative data analysis
  • Process of Qualitative data analysis
Module 14:Introduction to NVIVO
    NVIVO Key terms
  • NVIVO interface
  • NVIVO workspace
  • U= se of NVIVO ribbons
Module 15:NVIVO Projects
  • Creating new projects
  • Creating a new project
    • <= li>Opening and Saving project
  • Working with Qualitative data files
  • Importing Documents
  • Merging and exporting projects
  • M= anaging projects
  • Working with different data sources
Module 16:Nodes in NVIVO
  • Theme codes
    • <= li>Case nodes
  • Relationships nodes
  • Node matrices
  • Typ= e of Nodes,
  • Creating nodes
  • Browsing Nodes
  • Creating = Memos
  • Memos, annotations and links
  • Creating a linked memo
Module 17:Classes and summaries
    <= li>Source classifications
  • Case classifications
  • Node classif= ications
  • Creating Attributes within NVivo
  • Importing Attribu= tes from a Spreadsheet
  • Getting Results; Coding Query and Matrix Que= ry
Module 18: Coding
  • Data-dr= iven vs theory-driven coding
  • Analytic coding
  • Descriptive co= ding
  • 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:Q= ueries using NVIVO
  • Queries for textual analys= is
  • Queries for exploring coding
Module 21: Buildin= g on the Analysis
  • Content Analysis; Descripti= ve, interpretative
  • Narrative Analysis
  • Discourse Analysis
  • Grounded Theory
Module 22: Qualitative Analysis Resu= lts 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 c= harts
  • Creating models and graphs to visualize connections
  • T= ree maps and cluster analysis diagrams
  • Display your data in charts<= /li>
  • Create models and graphs to visualize connections
  • Create re= ports and extracts
Module 24: Triangulating results and So= urces
  • Triangulating with quantitative data
  • Using different participatory techniques to measure the same indicato= r
  • Comparing analysis from different data sources
  • Checking t= he consistency on respondent on similar topic
Module 25: R= eport Writing
  • Qualitative report format
    • <= li>Reporting qualitative research
  • Reporting content
  • Interpr= etation
MODULE 26:Basics of Applied Statistical Modelling = using R
  • Introduction to the Instructor and Co= urse
  • Data & Code Used in the Course
  • Statistics in the R= eal World
  • Designing Studies & Collecting Good Quality Data
    • =
  • Different Types of Data
MODULE 27: Essentials of the R= Programming
  • Rationale for this section
    • <= li>Introduction to the R Statistical Software & R Studio
  • Differ= ent Data Structures in R
  • Reading in Data from Different Sources
  • Indexing and Subletting of Data
  • Data Cleaning: Removing Missin= g Values
  • Exploratory Data Analysis in R
MODULE 28:= Statistical Tools
  • Quantitative Data
  • = Measures of Center
  • Measures of Variation
  • Charting & Gra= phing Continuous Data
  • Charting & Graphing Discrete Data
    • Deriving Insights from Qualitative/Nominal Data
MODULE 29= : Probability Distributions
  • Data Distribution= : Normal Distribution
  • Checking For Normal Distribution
  • Stan= dard Normal Distribution and Z-scores
  • Confidence Interval-Theory
  • Confidence Interval-Computation in R
MODULE 30: Stat= istical 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
MOD= ULE 31: Relationship between Two Different Quantitative Variables<= ul type=3D"disc">
  • Explore the Relationship Between Two Quantitative Vari= ables
  • Correlation
  • Linear Regression-Theory
  • Linear R= egression-Implementation in R
  • Conditions of Linear Regression
    • <= li>Multi-collinearity
  • Linear Regression and ANOVA
  • Linear Re= gression 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 an= d Non-linear regression
  • Linear Mixed Effect Models
  • Generali= zed Regression Model (GLM)
  • Logistic Regression in R
  • Poisson= Regression in R
  • Goodness of fit testing
    • MODULE 32= : Multivariate Analysis
    • Introduction Multivar= iate Analysis
    • Cluster Analysis/Unsupervised Learning
    • Princi= pal Component Analysis (PCA)
    • Linear Discriminant Analysis (LDA)
    • Correspondence Analysis
    • Similarity & Dissimilarity Across = Sites
    • Non-metric multi-dimensional scaling (NMDS)
    • Multivari= ate Analysis of Variance (MANOVA)
    Module 33: Report writin= g for surveys, data dissemination, demand and use
    • Writing a report from survey data
    • Communication and disseminat= ion strategy
    • Context of Decision Making
    • Improving data use = in decision making
    • Culture Change and Change Management
    • Pre= paring a report for the survey, a communication and dissemination plan and = a demand and use strategy.
    • Presentations and joint action planning<= /li>
    General Notes
    • All our course= s can be Tailor-made to participants needs
    • The participant must be = conversant with English
    • Presentations are well guided, practical ex= ercise, web based tutorials and group work. Our facilitators are expert wit= h more than 10years of experience.
    • Upon completion of training the = participant will be issued with Foscore development center certificate (FDC= -K)
    • Training will be done at Foscore development center (FDC-K) cen= ter in Nairobi Kenya. We also offer more than five participants training at= requested location within Kenya, more than ten participant within east Afr= ica and more than twenty participant all over the world.
    • Course dur= ation is flexible and the contents can be modified to fit any number of day= s.
    OTHER UPCOMING WORKSHOPS (REGISTER FOR THE COURSE AS IN= DIVIDUAL OR GROUP)








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