- Statistics and Probability Knowledge Checklist
- Top 18 Probability and Statistics Interview Questions for Data Scientists
- What Is the Difference Between Descriptive and Inferential Statistics?
- What Are the Main Measures Used to Describe the Central Tendency of Data?
- What Are the Main Measures Used to Describe the Variability of Data?
- What Are Skewness and Kurtosis?
- Describe the Difference Between Correlation and Autocorrelation
- Explain the Difference Between Probability Distribution and Sampling Distribution
- What Is the Normal Distribution and How Is It Characterized?
- What Are the Assumptions of Linear Regression?
- What Is Hypothesis Testing?
- What Are the Most Common Statistical Tests Used?
- What Is the P-Value and How Can We Interpret It?
- What Is the Confidence Interval?
- What Are the Main Ideas of the Law of Large Numbers?
- What Is the Central Limit Theorem?
- What's the Difference Between Population and Sample in Data Analysis?
- The Difference Between Probability and Likelihood
- What's Your Knowledge of Statistics, and How Have You Used it as a Data Analyst?
- How to Data Scientists Use Statistics?
- General Interview Tips & Tricks
- Probability and Statistics Interview Questions for Data Scientists: Next Steps
How to Create a Power BI Heatmap
How to Create a Power BI Heatmap Understand all the ins and outs of how to create Power BI heatmaps and their applications What are Data Visualization Heatmaps? Heatmaps were originally introduced by Cormac Kinney to graphically represent real-time financial information. They are used in data visualization to measure the intensity of given business values, encoded using different colors. The following image is an example of the heatmap, shared by NASA on July 13th, 2022. It shows the surface air temperatures for many countries in the world. The hottest the area is, the darkest the color. Investly, the coldest, the color is more driven towards blue. Such information can be easily understood at a glance. Data Scientists can use them to turn companies' information into easy-to-understand visualizations to help them make actionable smart decisions. As a Data Scientist, being able to provide businesses with a clear and concise visualization can help them grab ke...
Comments
Post a Comment