The relationship between sample and population is key in statistics. Samples allow researchers to estimate population characteristics without studying everyone. Variations between samples, called sampling variability, are natural but can be managed using concepts like the Central Limit Theorem, enabling accurate inferences about populations.
Statistical inference helps us make sense of data and draw conclusions about larger groups by analyzing smaller samples. It uses descriptive and inferential methods to find patterns, test ideas, and predict outcomes. Probability plays a key role by helping us handle uncertainty and make better decisions based on data.
mathematical thinking enhances data analysis by breaking down problems, identifying patterns, and choosing the right tools, from spreadsheets for small data to SQL for big data. Discover practical insights for data-driven decision-making in various contexts.
There are three dashboard types: Strategic for long-term goals, Operational for real-time performance tracking, and Analytical for data analysis and predictions, often used by data scientists.
Tableau There are many different visualization tools available i.e. to create a dashboard. One of the most powerful is Tableau,
Dashboards are powerful visual tools that help you tell your data story. A dashboard is a tool that monitors live,
