Design Principles for Data Analysis
Learning Objectives
- Compare convergent and divergent thinking
- Describe 6 design principles for data analysis
- Identify which principles were likely prioritized for given analyses
Statistical thinking
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
Statistical thinking
https://onishlab.colostate.edu/summer-statistics-workshop-2019/which_test_flowchart/
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Thinking
Model proposed by the Hasso-Plattner Institute of Design at Stanford
Design Principles
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
D’Agostino McGowan, Peng, and Hicks (2022) doi.org/10.1080/10618600.2022.2104290
