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Research Methodology, Data Management, Analyses and reporting using SPSS

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 SPSS as the primary software and Excel, ODK and Quantum GIS as complimentary software.

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)
  • 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
  • Use GIS software to plot and display data on basic maps
  • 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. The training is designed for participants who are reasonably proficient in English.

TOPICS TO BE COVERED

Day 1: Basic statistical terms and concepts

  • Introduction to statistical concepts
  • Descriptive Statistics
  • Inferential statistics

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

Day 2: 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

Software for Data Processing, management and GIS mapping

  • Data collections methods (Web, SMS, Mobile, Email, Social Media)
  • Use of ODK 2 for Mobile Data Collection
  • Importing ODK data into SPSS and Excel
  • Exercise: ODK exercise.

Day 3: Introduction to Data management and analysis using SPSS and Excel

Introducing Advanced analysis using SPSS

  • Overview of SPSS
  • Introduction to stat transfer for converting data into other formats
  • Exercise: Importing survey data into formats suitable for the reviewed software

Exploring survey data

  • Introduction to Excel for Data processing and Analysis
  • Data Auditing and Validation using Excel
  • Limitations of Excel
  • Basic exploratory data analysis procedures using SPSS
  • Basic data quality checks using SPSS

Tabulating and graphing survey data

  • Tabulation and analysis planning
  • File structure and datasets for tabulation and analysis
  • Basics of graphing
  • Simple Tabulations and Graphics using Excel
  • Advanced Tabulations and Graphics using SPSS and Excel
  • Exercise: Preparing suitable tables and graphics from the survey data using SPSS and Excel

Day 4: Data Management (SPSS and Excel)

  • Import, Export, load and save datasets
  • Create new datasets
  • Review and document the dataset
  • Sorting and ordering
  • Appending, merging and reorganizing datasets
  • Validate data structure
  • Identify duplicate observations
  • Exercise: Data management for the survey data

Day 5: Advanced Data Analysis with SPSS Part I

Statistical Inference

Correlation  

  • Correlation
  • Subgroup Correlations
  • Scatterplots of Data by Subgroups
  • Overlay Scatterplots
  • Exercises

Regression and Multiple Regression

  • Regression
  • Multiple Regression
  • Exercises

Comparing Means Using t-tests 

  • One Sample t-tests
  • Paired Sample t-tests
  • Independent Samples t-tests
  • Exercises

Comparing Means Using One-Way ANOVA 

  • One-Way Anova
  • General Linear Model to Calculate One-Way ANOVAs
  • Exercises

Comparing Means Using Factorial ANOVA 

  • Factorial ANOVA Using GLM Univariate
  • Simple Effects
  • Exercises

Comparing Means Using Repeated Measures ANOVA 

  • Using GLM Repeated Measures to Calculate Repeated Measures ANOVAs
  • Multiple Comparisons
  • Exercises

Chi-Square 

  • Goodness of Fit Chi Square All Categories Equal
  • Goodness of Fit Chi Square Categories Unequal
  • Chi Square for Contingency Tables
  • Exercises

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

Day 6 and 7: Advanced Data Analysis Part II (SPSS)

Regression analysis

  • The Problems with regression models
  • Ordered logistic regression
  • Multinomial logistic regression
  • Poisson regression
  • Two stage least square regression
  • GLM Model
  • Exercise: Modeling the survey data

Introduction to panel data analysis

  • Advantages of panel data analysis
  • Panel data sets
  • Balanced and unbalanced panels
  • Panel data dimensions and frequencies
  • Properties of estimators
  • Graphing panel data

Cluster Analysis

  • How Does Cluster Analysis Work?
  • Types of Data Used for Clustering
  • What to Look at When Clustering
  • Methods
  • Distance and Standardization
  • Example I: Hierarchical Cluster Analysis
  • Cluster Results
  • Obtaining Mean Profiles of Clusters
  • Relating Clusters to Other Variables
  • Summary of First Cluster Example
  • Example II: K-Means Clustering
  • Running K-Means Clustering

Factor Analysis

  • Introduction to Factor Analysis
  • Factor Analysis Versus Principal Components
  • Number of Factors
  • Rotation
  • Factor Scores & Sample Size
  • Methods
  • Looking at Correlations
  • Principal Components Analysis with an Orthogonal Rotation
  • Principal Axis Factoring with an Oblique Rotation

Day 8: Data visualization using infographics

  • Designing and making infographics
  • Common infographic styles
  • Infographics plan and layout
  • Making of charts
  • Making of maps
  • Making an infographic

Day 9: 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.

 Day 10: 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

REQUIREMENTS

Participants should be reasonably proficient in English. Applicants must live up to Indepth Research Services (IRES) admission criteria.

METHODOLOGY

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

ACCREDITATION

Upon successful completion of this training, participants will be issued with an Indepth Research Services (IRES) certificate.

TRAINING VENUE

The training is residential and will be held at IRES training Centre. The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

ACCOMMODATION

Accommodation is arranged upon request. For reservations contact the Training Officer.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it..  

Mob: +254 715 077 817

Tel: 020 211 3814

TAILOR- MADE

This training can also be customized for your institution upon request to a minimum of 4 participants. You can have it delivered in our training centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817, +254 (020) 211 3814 or mail This email address is being protected from spambots. You need JavaScript enabled to view it.

PAYMENT

Payment should be transferred to IRES account through bank on or before C.O.B. 9th September 2019.

Send proof of payment to This email address is being protected from spambots. You need JavaScript enabled to view it.

CANCELLATION POLICY

Payment for the all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

1.     Participants may cancel attendance 14 days or more prior to the training commencement date.

2.     No refunds will be made 14 days or less to the training commencement date. However, participants who are unable to attend may opt to attend a similar training at a later date, or send a substitute participant provided the participation criteria have been met.

Please Note: The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

Event Properties

Event Duration 10 Days
Event Date 16-09-2019
Event End Date 27-09-2019
Cut off date 09-09-2019
Individual Price(Kenyan) KES 139,000
Individual Price (International) EUR 1,592
Individual Price(International in Dollars) USD 1,853
Location Nairobi, Kenya
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Contact Us

+254 715077817 | +254 792516000
outreach@indepthresearch.org
Westlands, Rhapta Road
Njema Court, Suite R2

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