Training Course on Data Management, Graphics and Statistical analysis using SPSS
Introduction
SPSS is extensively applied in virtually every field including in government, business, and academia. It is a statistical analysis tool that allows any firm or individual to analyze huge chunks of data in order to understand it. The most common use of SPSS is to draw correlations between variables and to make statistically valid forecasts for future results.
Everything in our course is intended to making you a speedier and more casual SPSS user. Our courses are purposely pro-active including a lot of practical activities and examples to guarantee your proficiency in SPSS. We trust that product abilities that are created in practical situations are more profound than those created from classroom explanations. Our activities are precisely chosen to stress the key parts of every lesson.
Course Duration
5 Days
Course Objectives
i. Convert data into different formats using appropriate software
ii. Correctly identify appropriate statistical test for basic analysis s and perform them using SPSS
iii. Design computer-aided data capture screens using CSPRO
iv. Perform basic time series, longitudinal, and econometric analysis
v. Perform basic data analysis tasks with SPSS
vi. Perform simple to complex data management tasks using SPSS
vii. Appropriately use and understand and statistical terms and concepts
viii. Use mobile phone data collection tool Open Data Kit (ODK) to collect survey data
Course Content
Module I: An overview of SPSS
a. Basic data quality checks
b. Basic Descriptive Statistics
c. Basic exploratory data analysis procedures
d. Basic statistical terms and concepts
e. Common inferential statistics
f. Concepts and Software for Data Processing
g. Creating and editing a data file
h. Data Processing using Surveys Processing Software (CsPro) and Census
i. Editing output
j. Frequently –used dialog boxes
k. Mouse and keyboard processing
l. Opening file and file extensions
m. Printing results
n. The core functions of inferential statistics
o. Use of Mobile Phones for Data Collection and Processing
Module II: Data Entry, management and Manipulation
a. Define and label variables
b. Enter categorical and continuous data
c. Exploring data Selecting and sorting cases
d. Help files
e. Merging files
f. Replacing missing values
g. Restructuring data
h. Syntax and output
i. Transform, recode and compute variables
j. Tabulations and Graphics
k. Creating and editing graphs and charts
l. Cross Tabulations
m. Frequency Tables
n. Graphing Qualitative data
o. Graphing Quantitative data
p. Stub and Banner Tables
Module III: Advanced Statistical Analysis
a. Correlation and simple linear regression
b. Data Reduction Methods
c. Introduction to Econometric Analysis
d. Introduction to estimation and hypothesis testing
e. Introduction to Longitudinal Analysis Using SPSS
f. Introduction to Time Series Analysis
g. One sample tests: sign, t-test, and signed rank tests
h. Quantitative Analysis using SPSS
i. Regression Analysis
j. Three or more samples
k. Two-sample tests: t-test, Mann-Whitney test
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.
Key Notes
i. The participant must be conversant with English.
ii. Upon completion of training the participant will be issued with an Authorized Training Certificate
iii. Course duration is flexible and the contents can be modified to fit any number of days.
iv. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
v. One-year post-training support Consultation and Coaching provided after the course.
Training Course on Processing and Analysis of Data for Surveys/Assessment (Methodology and Software)
Introduction
Advanced technologies in the field of data science are creating a great opportunity for the improvement of decision-making. The number of data gathering initiatives in the developing world is on the rise with the use of such methods such as baseline surveys, Socio- Food Security Surveys, Economic Surveys, Nutrition Surveys Demographic and Health Surveys, Employees surveys, Program Evaluation Surveys, customers and vendor satisfaction surveys, and opinion polls being the most used. It is essential to involve and enhance individual human judgement in actual development concepts rather than just merely generating new insights from data.
This course takes this into consideration by empowering participants with the necessary skills for the production of accurate and cost-effective data that is useful and responsive for decision-making.
The training targets participants with basic knowledge of statistics from the fields of Economics Agriculture, Economics, Nutrition, Food Security and Livelihoods, Education, and Medical or public health, who intend to be conversant with the applications and concepts of statistical modelling. It is required that the participants have a basic knowledge of English.
Duration
5 days
Course Objectives
- Converting data into various formats by the use of appropriate software
- Correctly identifying appropriate statistical test for basic analysis and performing them by the use of SPSS/Stata or R
- Design and Implement universally acceptable Surveys
- Using Google Doc and Google maps in the collaboration and sharing of information.
- Put strategies to improve data demand and use in decision making.
- Using GIS software in plotting and displaying data on basic map.
- Write reports from survey data.
- Understanding and appropriately using statistical terms and concepts.
- Use mobile data gathering instruments such as Open Data Kit (ODK)
Course Content
Module I: Basic statistical terms and concepts
- Introduction to statistical concepts and GIS for Researchers
- Research Design
- Sources of Data for Social Statistics
- Planning, implementing and completing surveys
Module II: Concepts and Software for GIS mapping, Data Processing, and management
- Data collections method
- GIS mapping for Survey data
- Use of Mobile Phones for collecting and processing (ODK).
Module III: Introduction to Data management and analysis using Ms Excel
- Exploration of survey data using Excel
- Limitation of Excel
- Tabulating and graphing survey data using Excel
Module IV: Quantitative Data Analysis using SPSS/Stata/R
- Survey data management
- Graphing survey data
- Introducing Advanced Statistical software (SPSS, Stata and R)
Module V: Advanced Data Analysis, reporting, dissemination and use
- Introduction to panel data analysis (SPSS/Stata/R)
- Regression analysis (SPSS/Stata/R)
- Report writing for surveys, data dissemination, demand and use
- Statistical Inference (SPSS/Stata/R)
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.
Key Notes
- The participant must be conversant with English.
- Upon completion of training the participant will be issued with an Authorized Training Certificate.
- Course duration is flexible and the contents can be modified to fit any number of days.
- The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
- One-year post-training support Consultation and Coaching provided after the course
Training Course on M&E,Data Management and Analysis for in Food Security and Nutrition Programs
Introduction
The interest for information on the effect of approaches, projects and interventions on food and nutrition security is growing rapidly. The public sector, including the civil society and governments, frequently monitor data on food and nutrition in order to determine the existing trends and conditions, and the impact of interventions and policies.
International agencies, NGOs, governments and other agencies carry out monitoring, evaluation, and impact assessments regularly. With regard to this fact, this course lays emphasis on the need to carefully select the right set of indicators when designing information support systems at various administrative levels as well as the skills required for the analysis and interpretation of collected data.
The course adopts and interactive training approach and provides participants the chance to learn from each other as well as from the expert facilitators.
Duration
5 days
Course Outcomes
i. Understand the role of food security and nutrition for attaining the MDGs
ii. Gain fresh insights on the values of participatory & learning-oriented design, monitoring, and evaluation with regard to food security and nutrition.
iii. To strengthen your competence in designing an M&E-system
iv. Have clear ideas for the improvement of M&E systems and impact assessment for food security and nutrition.
Course Content
Module I: Introduction
- Food Security frameworks and concepts M& E Fundamentals
- Data sources collection and use
- Defining a good M&E system
- Identifying the challenges that face Monitoring and evaluation in the Food Security and Nutrition sector
- Including M&E in food security program design
- Indicators
- M&E Frameworks
- M&E Plans
- Participatory M&E systems
- Relating Monitoring and evaluation to your project cycle
- What is M&E?
Module II: M&E Frameworks
- Developing and operationalizing M&E frameworks
- Linking M&E frameworks to indicators
- M&E Frameworks
- M&E Frameworks basics for Food Security and other programs
- M&E in Food Security and Nutrition context
- Monitoring results and impacts using a logical framework
- Using data
Module III: Gender M&E
- Exploring gender in M&E plans
- Gender considerations for data collection
- Introduction to M&E in Gender and Food Security
- Selecting indicators to measure gender-related outputs and outcomes
- Prioritizing gender in M&E plans
Module IV: Step by Step approaches to M&E
- Agree on and design core documents to setup an M&E system
- Agree on field monitoring data collection and management process
- Agree on Monitoring data analysis process
- Agree on process for monitoring data utilization and reporting
- Agree on process of evaluation management
- Agree on the principles and purpose of the project M&E system
- Establish project M&E system
- Review and revise M&E plans based on progress
Module V: ICT tools for data collection, monitoring and evaluation in food security and nutrition
- Case study
- Dashboards; data management analytics, and stakeholders’ access
- Data collection implementation models
- ICT innovations
- ICT tool for Data processing
- Key choice of application to collect data in rural areas
- Using Mobile phones for data collection
Module VI: Data demand for food security and nutrition programs
- Data demand
- Data use frameworks and key concepts
- Information availability
- Information use
Module VII: Introduction to Data analysis Food Security and Nutrition Programs
- Basic analysis
- Data analysis key concepts
- Types of variables
Module VIII: Summarizing data
- Graphs and charts for continuous variables
- Graphs and charts for dichotomous and categorical variables
- Graphs and charts for ordinal variables
- Numerical summaries for discrete variables
- Tables for categorical variables
- Tables for dichotomous variables
- Tables for ordinal variables
- Tabulations for summary statistics for continuous variables
Module IX: Introduction to qualitative data Analysis
- Coding the data
- Introduction to qualitative data analysis software (NVivo)
- Organizing your data
- Planning for qualitative data analysis
- Reviewing the data
Module X: Quantitative data Analysis
- Basics for statistical analysis
- Choosing the correct statistical test
- Comparison of Data analysis packages
- Confidence intervals
- Hypothesis testing
- Hypothesis testing versus confidence intervals
- Interpreting the data
- Planning for qualitative data analysis
- Testing for normality of data
- Tests of statistical significance
Module XI: Assessing Programme Impact on Food Security
- Impact Assessment in Programme Design
- Introduction to Impact Assessment
- Programme Design Implications
Module XII: Methods and Approaches for Assessing Impact
- Overview of Methods and Approaches
- Qualitative Methods
- Quantitative Methods: Household Surveys
- Quantitative Methods: Secondary Data
- Selecting Methods and Approaches
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.
Key Notes
- The participant must be conversant with English.
- Upon completion of training the participant will be issued with an Authorized Training Certificate
- Course duration is flexible and the contents can be modified to fit any number of days.
- The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
- One-year post-training support Consultation and Coaching provided after the course.
Training Course on Qualitative Data Management and Analysis with NVIVO
Introduction
Qualitative research is the perfect approach to deepening our understanding of different phenomenon. In the recent past, a large number of qualitative studies have been carried out. This type research produces large amounts data in textual format. Most of this data is collected using field notes and transcripts. In order to draw inferences, a lot of rigorous and time-consuming work.
This course participants to lessen this burden by introducing them to NVivo. NVivo is a software with helpful features such as rich tech capabilities, character-based coding, and multimedia functions that are important for managing qualitative data.
The training targets participants who wish to analyze rich and jam-packed qualitative data including individuals from the following fields: Sociology, Education, Agriculture, Food Security and Livelihoods, Economics, Medical or public health professionals, and Nutrition, among others. No prior Knowledge is required.
Duration
5 days
Course Objectives
- Create a project
- Create and use classifications
- Explore the function of NVivo
- Import and create sources – PDFs, media files data sets, documents, and social media
- Manage your project material with finds and collections
- Undertake deductive and inductive qualitative data coding using NVivo
Course Content
Module 1: NVivo and qualitative research
- NVivo key terms
- Qualitative Data
- Qualitative vs Quantitative
- Sources of Qualitative data
- The NVivo Workspace
- Types of Qualitative Data
Module 2: Getting Started with NVivo
- Creating a new project
- Importing Documents
- Opening and Saving project
- Working with Qualitative data files
Module 3: Working with Codes and Nodes
- Browsing Nodes
- Creating a linked memo
- Creating Memos
- Creating nodes
- Memos, annotations and links
- Type of Nodes,
Module 4: Summarizing the Data
- Creating Attributes within NVivo
- Getting Results; Coding Query and Matrix Query
- Importing Attributes from a Spreadsheet
Module 5: Visualize your project
- Create models and graphs to visualize connections
- Create reports and extracts
- Display your data in charts
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.
Key Notes
- The participant must be conversant with English.
- Upon completion of training the participant will be issued with an Authorized Training Certificate
- Course duration is flexible and the contents can be modified to fit any number of days.
- The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
- One-year post-training support Consultation and Coaching provided after the course.