share data through the art of visualization coursera answers
Looking for ‘share data through the art of visualization course challenge answers? This guide provides all the solutions for Course 6 in the Google Data Analytics Professional Certificate. Whether you’re preparing for quizzes or the course challenge, these answers come with explanations to deepen your understanding.
Below, you will find all the modules in this course series, which include complete, accurate answers along with detailed explanations to help you grasp the core concepts.
Week 1 – Visualizing data
share data through the art of visualization weekly challenge 1 1. A data analyst wants to create a visualization that demonstrates how often data values fall into certain ranges. What type of data visualization should they use? Answers Line graph Scatter plot Histogram Correlation chart 2. What do correlation
Week 2 – Creating data visualizations with Tableau
share data through the art of visualization weekly challenge 2 1. Tableau is used to create interactive and dynamic visualizations. A visualization is interactive when the audience can control what data they see. What does it mean for a visualization to be dynamic? Answers The visualization can change over time
Week 3 – Crafting data stories
share data through the art of visualization weekly challenge 3 1. A data analyst wants to communicate to others about their analysis. They ensure the communication has a beginning, a middle, and an end. Then, they confirm that it clearly explains important insights from their analysis. What aspect of data
Week 4 – Developing presentations and slideshows
share data through the art of visualization weekly challenge 4 1. A data analyst gives a presentation about predicting upcoming investment opportunities. How does establishing a hypothesis help the audience understand their predictions? Answers It describes the data thoroughly It summarizes the findings succinctly It visualizes the data clearly and
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Related content Answers:
Course 1: Foundations: Data, Data, Everywhere
Course 2: Ask Questions to Make Data-Driven Decisions
Course 3: Prepare Data for Exploration
Course 4: Process Data from Dirty to Clean
Course 5: Analyze Data to Answer Questions
Course 7: Data Analysis with R Programming
Course 8: Google Data Analytics Capstone: Complete a Case Study
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