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Deriving Insights from Evidence (2225.YR.014923.1)

General information

Type:

BAS

Curs:

2

Period:

S semester

ECTS Credits:

5 ECTS

Teaching Staff:

Group Teacher Department Language
Year 2 María Galli Marketing ENG

Prerequisites

- CA02: Expressive Clarity
- CA04: Applied Creative & Critical Thinking
- CA07: Statistical Intuitions & Applications (co-requisite)

Workload distribution

The distribution of your workload will be (roughly) as follows:
- Active and Positive contribution in the classroom: 50% (including Pre-class work and Polls)
- Assignments: 25%
- Quizzes and Final Exam: 25%

COURSE CONTRIBUTION TO PROGRAM

Students in this course learn to combine creative and critical thinking to quantitatively apply methods used in the natural and social sciences. Students learn to frame problems effectively, develop and test hypotheses, and derive insights from empirical evidence. Students will dig deeply into different types of data; comparing cases in which direct manipulation of the phenomena being studied is not possible (such as observational studies, case studies, and surveys), and cases in which variables are manipulated to different degrees (such as randomized controlled medical trials and quasi-experiments). We emphasize the tenets of good research design, strengths and limitations of different design types, quantitative methods to validate data, and the generalizability of inferences drawn from distinct study designs.

Course Learning Objectives

By the end of the course, students should be able to:

- In terms of developing ideas about how things work:
· Analyze and apply deductive logic
· Identify and appropriately structure the information needed to support an argument effectively
· Evaluate the link between hypothesis-driven research and the theories or observations that motivate it
· Analyze and apply inductive reasoning
· Identify and classify the relevant variables of a system, problem, or model

- In terms of interpreting evidence:
· Apply and interpret measures of correlation; distinguish correlation and causation
· Interpret, analyze, and create data visualizations
· Calculate and interpret descriptive statistics appropriately
· Recognize how models can be used to explain a set of data and generate new predictions
· Design effective sampling methods and evaluate the interpretation of results accordingly

- In terms of testing ideas:
· Identify and evaluate appropriate control groups for empirical study designs
· Apply and interpret experimental studies
· Design and interpret primary research performed as interviews or surveys (individually or in groups)
· Design and interpret observational studies

CONTENT

1. Unit 1: Scientific Method

This unit explores the scientific method. It begins with the foundations of empiricism: observations, perceiving patterns, formulating hypotheses about future observations, and testing those hypotheses. Students learn that observations are theory-driven, how values and contexts inform what we observe, and what kinds of patterns we seek. We discuss the desirable properties of scientific hypotheses, including testability, accuracy, simplicity, consistency, and fruitfulness. We also explore the relationships among facts, hypotheses, theories and scientific laws. We use scientific research that explores aspects of the Big Questions such as ¿Are humans the primary cause of modern-day climate change?¿ and ¿How did our Universe evolve?¿ as context to explore the scientific method.

2. Unit 2: Data Visualizations and Modeling

Models can describe a system, test hypotheses, or be used to derive predictions and hypotheses. In this unit, students explore different types and uses of models, which can be the research project itself or be one tool used in a research project. Testing the same hypotheses using a model, an observational study, and an interventional study provides strong evidence. We use scientific research, models, and computer simulations addressing a Big Question such as ¿How can we avoid global pandemics?¿ to explore these concepts and give them context.

3. Unit 3: Research Design

This unit is a survey of major types of study design applied in the natural and social sciences. Students design research studies and evaluate research design in primary literature. We explore data collection for cases in which direct manipulation of the phenomena being studied is not possible (e.g., observational studies, case studies, surveys), and examples in which variables are manipulated to different degrees (e.g., randomized controlled medical trials, quasi-experiments). Emphasis is on the tenets of good research design, strengths and limitations of different design types, generalizability of inferences drawn from different study designs, and practice designing, applying and evaluating research studies. We use and evaluate primary literature exploring aspects of Big Questions such as ¿How do humans impact evolution?¿ and ¿Why do we age?¿ to explore these concepts and give them context.

4. Unit 4: Synthesis: Problematic Applications

In addition to the problems covered in the biases and research design units, sociological factors are at work even in well-intentioned and responsible people, which influence what kinds of science are funded, what questions get attention, what is published, and what makes an impact. In this unit we also review a range of problematic and/or atypical examples of the application of science. This includes exploration and examples of pseudo-sciences, underlying reasons for scientific retractions, bad applications of the scientific method, and cases when establishment views are overthrown or replaced in scientific revolutions. We revisit examples from previous Big Questions to provide context through this unit.

Methodology

This course combines lectures with group discussions and in-class exercises. Your active participation is essential. Sharing your thoughts, experience, and insights with the group will enrich the sessions and contribute to all participants' learning experience.

A learning area will be available in the Intranet. There, you would find instructions for the sessions, communications, bibliography, etc. Please consult it often.

Assessment criteria

- Active and Positive contribution in the classroom: 50% (including Pre-class work and Polls)
- Assignments: 25%
- Quizzes and Final Exam: 25%

Bibliography

There is no required textbook for this course. Any readings, notes, handouts, dataset or additional course material will be available through the course website.

Timetable and sections

Group Teacher Department
Year 2 María Galli Marketing

Timetable Year 2

From 2022/9/9 to 2022/10/28:
Monday and Friday from 9:00 to 10:30. (Except: 2022/9/26, 2022/10/3, 2022/10/10, 2022/10/17 and 2022/10/24)

Wednesday 2022/9/28 from 9:00 to 10:30.

From 2022/10/3 to 2022/12/5:
Each Monday from 9:00 to 10:30.

From 2022/11/11 to 2022/12/2:
Each Friday from 9:00 to 10:30.