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Research Design, Data Management And Statistical Analysis Using SPSS . by FINERESULTS(m): 10:39am On May 09, 2020
FineResults Research Services invites you to training on:

Topics: Research Design, Data Management and Statistical Analysis using SPSS

Date: 17th to 28th August 2020

Cost: USD 1600 or Ksh 120,000

Contacts: +254 759 285 295, training@fineresultsresearch.org

Venue : FineResults Research, Nairobi, Kenya Training Centre.

INTRODUCTION
SPSS is a complete statistical software package for data management, data analysis and graphics. Using the software classical and advanced functions, SPSS software can be used via a graphical user interface (menus and dialog boxes) or a using syntax command. Besides equipping the participants with advanced data management and analysis using SPSS, this 10 days course aim to introduce participants to research design, sampling techniques and report writing skills all aimed at helping the participants to understand the research process all through to decision making.

COURSE DURATION
10 Days

TARGET PARTICIPANTS
Government institutions, research institutions and NGOs and any other person interested in advancing data analysis skills using SPSS software

COURSE OBJECTIVES
By the end of the training, you will be able to:
• Understand and appropriately use statistical terms and concepts
• Design both quantitative and qualitative data collection tools
• Understand both descriptive and inferential statistics
• Understand various data collection techniques and data processing methods
• Use basic functions and navigation within SPSS
• Create and manipulate graphs and figures in SPSS
• Execute syntax
• Use SPSS effectively for manipulating and analysing data.
• Export the results of your analyses.
• Learn interpretation of results
• Learn how to write different research outputs including project reports, case studies, evidence briefs, policy briefs, posters among other outputs

TOPICS TO BE COVERED
Module 1: Introduction to research
Basic statistical terms and concepts
• Introduction to research
• Introduction to statistical concepts
• Descriptive Statistics
• Inferential statistics

Research Design
• The role and purpose of research design
• Types of research designs
• The research process
• The survey process
• Survey design
• Sampling techniques and sample size determination
• Developing research protocol

Module 2: Research Approaches
• Quantitative Research Approaches
• Qualitative Research Approaches

Data Collection Methods in Research
• Quantitative data collection methods- Developing of quantitative data collections tools in paper
• Qualitative data collection- Developing qualitative data collection tool
• Developing research protocol

Module 3: Mobile Data Collection and Processing using open data kit (ODK)
• Introduction to mobile data gathering
• Designing a questionnaire in ODK
• Design of survey forms using ODK build and XLS Form
• Use ODK collect to gather data
• Use ODK aggregate to upload data to the server
• Download data for data analysis
• Exporting data to SPSS

Module 4: Introduction to SPSS statistical software
• SPSS interface and features (Data editor, syntax, output, chart editor etc)
• Data file preparation, cleaning, sorting, coding, recoding, missing values)
• Data entry into SPSS
• Data manipulation: merge files, spit files, sorting files, missing values

Basic Statistics using SPSS
• Descriptive statistics for numeric variables and categorical variables
• Frequency tables
• Distribution and relationship of variables
• Cross tabulations of categorical variables

Module 5: Statistical Tests using SPSS
• One Sample T Test
• Independent Samples T Test
• Paired Samples T Test
• One-Way ANOVA

Statistical Associations in SPSS
• Chi-Square test
• Pearson's Correlation
• Spearman's Rank-Order Correlation

Module 6: Regression analysis using SPSS
• 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
• Linear Regression
• Multiple Regression

Module 7: Other types of regression analysis
• Logistic Regression (Probit, logit regressions)
• Ordinal Regression
• Poison regressions
• Multinomial logit/probit regression

Module 8: Report writing
• Survey report format
• Survey report content
• Use of survey findings for decision making

Module 9: Writing case study,
• What is a case?
• Structure of a case?
• Case writing guidelines?
• Case selection?

Elements of a good case
• Simplifying writing
• Good writing
• Easy-to-read writing
• Four ways to start writing
• Writing sample cases

Module 10: Writing a policy brief
• What is a policy brief
• Purpose of policy brief
• Characteristics of good policy briefs
• Structural guidelines for presentation
• Key elements of a policy brief
• Technical guidelines for presentation of policy briefs

NB: We are offering you a half day, fun and interactive team building event!

Be part of the Training
• Click HERE for the individual registration.

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