In this lesson, students will explore how data is used in the social sector. They will use this information to help formulate at least three problem statements each with two statistical questions.
Students will be able to:
In this lesson, students will learn about big data and cognitive biases. They will reflect on their own potential biases and work forward on their project by finding and considering datasets and further decomposing their problem statement.
Students will be able to:
In this lesson, students will learn how to import large datasets. They will also learn how to filter a dataset using index-based selection (iloc) and label-based selection (loc).
Students will be able to:
iloc and locIn this lesson, students will learn how to conditionally filter a dataset using label-based selection (loc) and comparison operators.
Students will be able to:
locIn this lesson, students will learn the importance of data cleaning and how to do it. Data cleaning deals with fixing or removing incorrect or missing values.
Students will be able to:
In this lesson, students will explore datasets using visualizations such as pie charts, boxplots, histograms, and scatterplots.
Students will be able to:
In this lesson, students will work on analyzing, explaining, and presenting conclusions found in their data exploration.
Students will be able to:
In this lesson, students review content with a 10 question end-of-module quiz.
Students will be able to:
