Source
https://www.udemy.com/course/research-methodology-complete-research-project-blueprint/
Category
File Size
2 GB
Publisher
udemy
Updated
June 26, 2023
Description
- The Three Elements of an Intriguing Research Question.
- How to Formulate an Intriguing Research Question.
- A Simple Template For Your Research Question.
- How to Define The Variables in Your Research Question.
- The Four Elements of Strong Methodology.
- Which Methodology to Use? Qualitative vs Quantitative.
- How Your Research Design Affects the Interpretation of Your Findings.
- Inferring Causation – How to Avoid This Common Mistake!
- The Most Effective Way to Rule out Alternative Explanations.
- Types of Research Designs.
- How to Avoid Unnecessary Complexity in Your Research Design.
- Why You Need to Randomize (And How).
- Experimental And Non-experimental Designs.
- Confounders in Research Designs.
- How to Design Successful Non-Experimental Studies.
- How to Make Your Variables Measurable.
- The Two Elements of an Effective Measurement.
- A Simple Trick To Boost The Reliability of Your Measurements.
- Types of Measurements – Which One is Right for You?
- What to Do If Your Variables Cannot Be Measured Accurately (Simple Hack).
- The Three Elements of Good Data Collection.
- Data Collection Strategies And When To Use Which.
- Sample size – How Many Participants Do You Need?
- The Three Steps of Data Analysis.
- Master Free And Easy-to-use Software for Data Analysis (JASP).
- Data Preparation STEP 1: Import and Format Your Data.
- Data Preparation STEP 2: Deal With Missing Values.
- Data Preparation STEP 3: Handle Outliers (Tricky).
- How to Analyze Data with a Numerical IV and Numerical DV (Step-by-step).
- How to Analyze Data with a Categorical IV and Numerical DV (Step-by-step).
- How to Analyze Data with a Numerical IV and Categorical DV (Step-by-step).
- How to Analyze Data with a Categorical IV and Categorical DV (Step-by-step).
- How to Generalize to a Population.
- The Three Principles Behind Every Statistical Test.
- The One Number You Need to Generalize Your Findings.
- How to Use Inferential Statistics (Step-by-step).
- Generalizing a Correlation.
- Generalizing a Difference Between Groups (ANOVA).
- Generalizing a Difference Between Moments in Time (RM ANOVA).
- Generalizing in a Mixed Design (RM ANOVA).
- Generalizing a Continuous Effect on Probabilities (Logistic Regression).
- Generalizing a Difference Between Probabilities (Chi Square Test).
- Avoid Mistakes! Two Common Mistakes and How to Prevent Them.
- The Two Types of Statistical Errors – And How to Minimize Them.
- How to Select The Right Sample Size (Power Analysis).
- Master Free and Easy-to-use Software For Sample Size Calculation (G*Power).
- Sample Size Calculation For Correlations.
- Sample Size Calculation For ANOVAs.
- Sample Size Calculation For Logistic Regression.
- Sample Size Calculation For Chi Square Tests.
- Three Simple Strategies to Maximize Your Statistical Power.
- How to Test the Reliability of Your Measurements.
- How to Test the Validity of Your Measurements.
- Conducting Your Research: Essential Parts That You Do Not Want to Miss in Any Research Study.
- Recruiting: How To Find Participants.
- Incentives: How To Motivate People to Participate.
- The Four Steps of Interpreting Findings.
- How to Interpret Results in an Experimental Design.
- How to Interpret Results in a Quasi-Experiment.
- How to Interpret Results in a Non-Experimental Design (Categorical IV).
- How to Interpret Results in a Non-Experimental Design (Numerical IV).
- How to Interpret Results in a Non-Experimental Design (Categorical IV and DV).
- How to Interpret a Null-result.
- How to Fix Methodological Problems Even After Your Study is Already Conducted.
- And more!
- In short, you will learn specifically why, what, when, where, and how to perform research.
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