Research Design and Data Analysis for Experimental Studies Training Course

Research Design and Data Analysis for Experimental Studies Training Course

Gain the skills you need to advance your career. This course offers hands-on learning, expert guidance, and real-world applications designed to help you grow.

Intermediate | 10 days | Face to Face / Online / Elearning | Certificate
01

Course Overview

Course Summary
Course Title Research Design and Data Analysis for Experimental Studies Training Course
Organization Tech For Development (T4D)
Venue Tech For Development (T4D) Training Center along Tala Road, Runda, Nairobi
Duration 10 days
Target Industries
Target Job Roles
Course Fees (Face-to-Face) USD 2,200/KES 150,000 (Exclusive of VAT)
Course Fees (Virtual)
Training Modes Virtual and face-to-face training
Payment Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course
Accreditation Tech For Development Certificate of Course Completion

Course Overview

Data analysis is the application of one or more statistical techniques to a set of data as collected. In designed experiments, some form of treatment is applied to experimental units and responses are observed. This course is designed to transform participants into professional data analysts. It is designed for participants without or with very little experience using statistical software. Some basic knowledge on statistics is required. During the course, the instructors will interchangeably use Stata, Excel, SAS and SPSS to demonstrate relevant techniques in each topic.

Duration

10 Days

Target Audience

  • Researchers
  • Data Analysts and Statisticians
  • Program and Project Managers
  • Aspiring Researchers

Organizational Impact

  • Improved quality and reliability of research outcomes leading to better decision-making.
  • Enhanced research capabilities, leading to innovative solutions and product development.
  • Increased ability to meet regulatory and ethical standards in experimental research.
  • Strengthened capacity to conduct and analyze experimental studies efficiently, leading to cost savings.
  • Enhanced reputation through the production of high-quality, impactful research.

Personal Impact

  • Mastery of advanced research design and data analysis techniques.
  • Increased confidence in conducting and analyzing experimental studies.
  • Enhanced ability to critically evaluate the validity and reliability of research findings.
  • Improved problem-solving skills through the application of statistical methods to experimental data.
  • Greater career opportunities in research, academia, and industry.

Course Objectives

  • Understand Experimental Design and Variable Classification
  • Review Probability and Statistical Distributions
  • Conduct Exploratory Data Analysis (EDA)
  • Utilize Data Analysis Software
  • Perform Hypothesis Testing and ANOVA
  • Apply Regression Analysis Techniques
  • Implement Advanced ANOVA Techniques
  • Calculate and Improve Statistical Power
  • Explore Contrasts and Mixed Models
  • Analyze Categorical Data
02

Course Modules

Course Outline

Module 1: Introduction to Statistical Analysis

  • The importance of careful experimental design
  • Variable Classification
  • Overview of statistical analysis
  • Parametric Versus Nonparametric Analyses
  • Case Study: Designing an Experiment to Test a New Drug

Module 2: Probability and Distributions

  • Review of Probability
  • Common Distributions (Binomial, Poisson, Gaussian, etc.)
  • Parameters describing distributions (Central Tendency, Spread, etc.)
  • Central Limit Theorem
  • Case Study: Analyzing the Probability of Success in a Marketing Campaign

Module 3: Exploratory Data Analysis (EDA)

  • Univariate Non-Graphical and Graphical EDA
  • Multivariate Non-Graphical and Graphical EDA
  • Covariance and Correlation
  • Cross-Tabulation
  • Case Study: Exploring a Dataset from a Customer Satisfaction Survey

Module 4: Software Tools for Data Analysis

  • Overview of SPSS, Stata, Excel, and SAS
  • Data Entry and Import
  • Creating and Recoding Variables
  • Graphical and Non-Graphical EDA in Software
  • Case Study: Performing Data Analysis Using SPSS for a Retail Dataset

Module 5: Hypothesis Testing

  • t-Test (Independent and Paired)
  • One-Way ANOVA
  • Assumption Checking and Results Interpretation
  • Threats to Experiment Validity
  • Case Study: Comparing Customer Retention Rates Between Two Different Marketing Strategies

Module 6: Regression Analysis

  • Simple Linear Regression
  • Multiple Regression and Interaction
  • Analysis of Covariance (ANCOVA)
  • Regression Calculations and Interpretation
  • Case Study: Analyzing the Impact of Advertising Spend on Sales

Module 7: Advanced ANOVA Techniques

  • Two-Way ANOVA
  • Interpreting Two-Way ANOVA Results
  • Application Areas and Practical Examples
  • ANCOVA with Interaction
  • Case Study: Evaluating the Effect of Different Training Programs on Employee Performance

Module 8: Statistical Power and Effect Size

  • Understanding Statistical Power
  • Improving Power and Calculating Effect Sizes
  • Power Calculations for ANOVA and Regression
  • Practical Considerations for Power Analysis
  • Case Study: Planning a Study to Determine the Sample Size Needed for Reliable Results

Module 9: Contrasts and Mixed Models

  • Contrasts and Custom Hypotheses
  • Within-Subjects Designs and Paired t-Test
  • Mixed Models and Their Applications
  • Model Selection and Penalized Likelihood Methods
  • Case Study: Analyzing a Clinical Trial with Repeated Measures

Module 10: Categorical Data Analysis

  • Contingency Tables and Chi-Square Analysis
  • Logistic Regression
  • Testing Independence and Goodness-of-Fit
  • Predictions in Logistic Regression Models
  • Case Study: Predicting Customer Churn Using Logistic Regression
03

Course Administration

Methodology

Instructor-led sessions use a blended learning approach combining presentations, guided practical exercises, web-based tutorials, and group work, delivered by seasoned industry experts. All facilitation and course materials are in English, so participants should be reasonably proficient in the language.

Accreditation

Upon successful completion of this training, participants will be issued a Tech For Development Certificate of Course Completion certified by the National Industrial Training Authority (NITA).

Training Venue

The training will be held at the Tech For Development Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.

Accommodation & Airport Transfer

Arranged upon request.For reservations contact the Training Officer:
Email: [email protected]
Phone: (+254) 790 824 179

Tailor-Made

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our T4D Training Centre or at a convenient location.

Payment

Payment should be transferred to the T4D account through a bank on or before the start of the course. Send proof of payment to [email protected].

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