Methodology and Software for Processing and Analyzing surveys and Assessments data SPSS Stata Excel ODK

Date                                                               Event

17th to 21st May 2021                        Methodology and Software for Processing and Analyzing surveys and Assessments data SPSS Stata Excel ODK

Venue: FineResults Research Services, Nairobi, Kenya Training Centre.

Click to Register: Physical class USD 800

Contact us: email: [email protected] or Cell phone (+254 759 285 295)

INTRODUCTION

Research, Data Management, Graphics & statistical analysis has always been integral parts of development work and has been playing a critical role towards achieving of Sustainable development Goals (SDGs). As a result, knowledge of research methodologies and application of statistical application software's to support data analysis in this era is very important. Statistical Packages for Social Sciences (SPSS), Stata and Microsoft Excel software has proved to be quite useful for the purpose of data management, graphical representation, and statistical analysis of data. These software are user-friendly and reduces the time/efforts that the researcher employ in research. This course aims at equipping participants with knowledge and vast skills which will enable them to use SPSS, STATA and Microsoft Excel in data management, graphics and statistical analysis. At the end of the course, participants will become familiar with using ICT tools and methods to conduct data collection, statistical analysis and reporting.

DURATION

5 Days

LEARNING OBJECTIVES

By the end of the training, you will be able to:

• Understand both descriptive and inferential statistics
• Understand various data collection techniques and data processing methods
• Use mobile phones for data collection(Open data Kit)
• Use basic functions and navigation within Stata and SPSS software
• Create and manipulate graphs and figures in Stata and SPSS software
• Handle statistical data analysis tasks in Stata and SPSS software
• Export the results of your analyses.

TOPICS TO BE COVERED

Day 1:

Statistical Concepts

• Statistical Concepts
• Types of data

·         Data Structures and Types of Variables

• Overview of SPSS

Statistical Inference

·         Tests of Association

·         Tests of Difference

·         Hypothesis testing

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
• Questionnaire Design

Getting started in ODK

• Types of questions
• Data types for each question
• Types of questionnaire or Form logic
• Extended data types geoid, image and multimedia

Survey Authoring and Preparation of mobile phone for data collection

• Survey Authoring
• ODK Collect applications: Installing, Configuring the device (Mobile Phones) and uploading the form into the mobile devices

Designing forms and advanced survey authoring

• Introduction to XLS forms syntax
• New data types
• Notes and dates
• Multiple choice Questions
• Multiple Language Support
• Hints and Metadata

Advanced survey Authoring

• Conditional Survey Branching
  • Required questions
  • Constraining responses
  • Skip: Asking Relevant questions
  • The specify other
• Grouping questions
  • Skipping many questions at once (Skipping a section)
• Repeating a set of questions
• Special formatting
• Making dynamic calculations

Hosting survey data (Online)

• ODK Aggregate
• Uploading the questionnaire to the server

Day 2:

Introduction to SPSS/Stata/Excel

• Installing the software(s)
• Software interfaces
• Working with the software (file management, editing functions, viewing options, etc)
• Output Management
• Basics programming of Stata and SPSS

Data Entry/Management

• Entering categorical and continuous data
• Defining and labeling variables
• Validation and Sorting variables
• Transforming, recording and computing variables
• Restructuring data
• Replacing missing values
• Merging files and restructuring
• Splitting files, Selecting cases  and weighing cases
• Syntax and output

Descriptive Statistics

Measures of Variability and Central Tendency  

• Describing quantitative data
• Describing qualitative data

Graphics in Data Analysis

• Graphing quantitative data
• Graphing qualitative data
• Advanced graphics options

Day 3:

Quantitative Data Analysis (Part I)

Correlation  

• Correlation of bivariate data
• Subgroup Correlations
• Scatterplots of Data by Subgroups
• Overlay Scatterplots

Comparing Means

• One Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
• Comparing Means Using One-Way ANOVA 

Comparing Means Using Factorial ANOVA 

• Factorial ANOVA Using GLM Univariate
• Simple Effects

 Comparing Means Using Repeated Measures ANOVA 

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

Module 5: Quantitative Data Analysis (Part III)

 Chi-Square 

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

Day 4:

Quantitative Data Analysis (Part II)

Regression Analysis

• Assumptions of selected types of regression
• Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression
• GLM Model
• The Problems with regression

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

Day 5:

Quantitative Data Analysis (Part III)

Survey estimation and inference for complex designs

• Introduction to survey data
• Introduction to complex sample designs, survey estimation and inference
• Multi-stage designs, stratification, cluster sampling, weighting, item missing data, finite population corrections
• Models and assumptions for inference from complex sample survey data
• Sampling distributions, confidence intervals
• Design effects.

Advanced analysis of complex survey data

• Bayesian Analysis of Complex Sample Survey Data
• Generalized Linear Mixed Models (GLMMs) in Survey Data Analysis
• Fitting Structural Equation Models to Complex Sample Survey Data
• Small Area Estimation and Complex Sample Survey Data
• Nonparametric Methods for Complex Sample Survey Data

TRAINING CUSTOMIZATION

This training can also be customized for your institution upon request. You can also have it delivered your preferred location.

For further inquiries, please contact us through Mobile: (+254 759 285 295) or Email: [email protected] 

REQUIREMENTS

Participants should be reasonably proficient in English.  During the trainings, participants should come with their own laptops.

TRAINING FEE

The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.

CANCELLATION POLICY

• All requests for cancellations must be received in writing.
• Changes will become effective on the date of written confirmation being received.

Visit our website for more details

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