Training Programs

Training Programs

Indicators is trying to share in the capacity building in the field of analytics. In addition to increase the knowledge about research methods, tools, data analysis, and writing policy papers.
For these aims Indicators provides the following training programs:


Are you interested in one of our trainings?

You can sign up from here..

 Name of the training programThe most important axes
1Surveys -Polls: Types of surveys and their uses.
-Writing survey questions and ways to submit answers.
-Methods of collecting survey data strengths and weaknesses when we use each.
-Survey tool test (questionnaire).
-Methods of analysis of opinion polls data.
- Write a poll report.
2Skills of writing questionnaires-Questionnaires information forms and survey questions.
- Types of questions: strengths weaknesses, and uses.
- Writing questionnaire questions taking into account the determinants of the study.
- Answers: types, general guidance on the appropriate mix of answers.
- Quality and reliability tests of the questionnaire.
3Preview and sampling methodologies- Identify the study community.
- Studying the nature of society (its classes and assemblies).
- Review the objectives of the study and the corresponding sampling methods.
- Types of sampling and indicators of representative society.
- Sample mapping and distribution of categories.
4means of data collection- Data collection methods: field, electronic, interviews, Phone calls.
- strengths and weakness.
- When we use each mean of data collection.
5Data quality management- Data types.
- Quality control starting from the training of data collectors.
- Data collector monitoring tools.
- Data Validation Mechanisms.
- Data review and audit mechanisms.
- Data cleaning: lost data, abnormal and extreme data.
- Adjust the quality of data analysis outputs.
6Preparation of the field researcher- Confidence building skills with respondents.
- Mechanisms for asking questions and interviewing the respondent.
- Individual interviews.
- Expert interviews.
- Facilitate focused dialogue sessions.
- Field follow-up.
7Designing statistical studies projects.- Prioritization of statistical studies
- Mechanisms to develop the problem of the study and its objectives and hypotheses.
- Steps to conduct statistical studies.
- Field and financial follow-up models.
- Data quality verification procedures and follow-up of field researchers.
8Planning based on statistical studies- Effects of reliance on statistical studies and analyzes on the success of institutions.
- Planning tools and their uses.
- Use planning tools and statistical findings to build new policies and action plans.
- Writing policy papers (methodologies, literature, mechanisms for addressing decision makers).
9Statistical analysis using SPSS- Definition of statistical program SPSS.
- Enter data in the program.
- Statistical analysis tools descriptive.
- Analysis of multiple-answer questions.
- Intersection tables (pivot tables).
- Relationship analysis.
- Review and audit data.
- Data management (selection division arrangement).
- Data conversion (new column calculation recoding data handling lost values Graphs).
10Statistical analysis of questionnaires using SPSS- Questionnaires their uses how they are designed their literature.
- Data collection and unloading in the SPSS program.
- Test the quality and reliability of the questionnaire.
- Analysis of survey data using SPSS.
- Reporting basics.
11Analyzing data using Excel- Introducing Excel.
- Data Validation settings.
- Checking and cleaning data.
- The most important data analysis functions in Excel.
- Descriptive statistics using Excel.
- Charts in Excel.
- Pivot tables.
12Analysis of data using Excel Advanced level- Advanced options in Pivot tables.
- Interactive Reports Power view.
- Interactive tables and queries Power query.
- Interactive maps in Excel.
13Data Analysis and Interactive Reporting using Microsoft Power BI- Introduction to the program: its advantages and uses.
- Connect the program to databases online or from the computer.
- Software version on the desktop Power BI for Desktop.
- Data cleaning.
- Charts and tables and their main advantages.
- Design and publish reports.
- Manage automatic update of reports.
14basics of Monitoring and Evaluation- Designing Monitoring and Evaluation Process (Logical Framework and Indicator Matrix).
- Planning the monitoring and evaluation process.
- Monitoring and evaluation data sources.
- Stakeholder analysis risk analysis and use in monitoring and evaluation.
15Advanced M & E techniques- Sources of data collection: beneficiary questionnaires, experienced interviews, focused dialogue sessions.
- Monitoring and evaluation forms: types and how to design them.
- Building monitoring and evaluation indicators.
- Design matrix indicators.
- Writing monitoring and evaluation reports.
16Impact Analysis of Projects- Planning for impact analysis review of project objectives and initial completion reports.
- Building project impact measurement metrics and indicators.
- Mechanisms for analysis of external interventions.
- Analyze data and output results of impact analysis.
- Writing an impact analysis report.
17Human needs assessments- humanitarian needs assessment types:
- building humanitarian needs assessment plan.
- designing evaluation forms
-writing humanitarian needs reports
18Electronic Questionnaires using Kobo- characteristics and uses of Kobo software.
- Design questionnaires using the Kobo Tool Box.
- Test questionnaire and check designing errors.
- Implement the questionnaire and share it with the data collection team.
- Field interviews using the Kobo Collect application.
- Send data from the application to the main server.
- Export data from Kobo.
19Electronic questionnaires using Google forms- Advantages and uses of the Google forms platform.
- Types of questions in Google forms.
- Design questionnaires using Google forms.
- sharing questionnaire and management of authorities.
- Database preparation and export.
20Internal Auditing- What is TQM.
- The main aspects of ISO specifications.
- Six Sigma concept.
- Internal quality audit mechanisms and tools.
21SPSS Statistical Quality Control- Definition of quality management concepts.
- What is the statistical definition of quality and its benefits.
- Seven tools for statistical quality control.
- Use SPSS in quality control.
22Designing SOP procedures- Benefits of designing business processes
- Types of work procedures manuals
- General structure of the working procedures manual
- Language methods in writing the guide
- Mechanism for review adoption and dissemination of the Manual
- Update the procedures guide and follow up the update log
23Statistical Prediction- The most important statistical tools for predicting.
- Regression analysis: simple, multiple. advanced.
- Time chains.
- Test prediction methods.
24Statistical analysis of scientific research- Basic concepts on statistical tests.
- Designing experiments.
- Scientific statistical tests.
- Non-scientific statistical tests.
- Conducting statistical tests using the IBM SPSS program.