Introduction to Data Analysis: What is Data and Why Does It Matter?

Learning Objectives Define the term 'data' in their own words. Identify at least three different types of data (number, text, boolean). Explain why collecting data is important for making decisions. Give a real-world example of how data is used. Collect a small set of data and store it in variables. Distinguish between a single data point and a dataset. Ever wonder how a video game knows your high score or how Netflix suggests the perfect show for you? 🎮 It's all about data! In this lesson, we'll discover that data is just information we can collect. We will learn what data is, the different types of data, and why it's one of the most powerful tools for solving problems and making smart choices. Real-World Applications Video game leaderboards t...

TermDefinitionExample DataFacts and pieces of information that can be collected, measured, and analyzed.The heights of all the students in your class. Data PointA single piece of information or a single fact.One student's height is 150 cm. That '150 cm' is a data point. DatasetA collection of related data points.A list of the heights of all 25 students in your class is a dataset. Data TypeThe kind or category of a piece of data. Common types are numbers, text, and booleans (True/False).A player's score, `1250`, is a number. Their username, `"DragonSlayer"`, is text. VariableA container in coding used to store a data point. It has a name and a value.In code, you could store a player's score like this: `player_score = 1250`. Data AnalysisThe process of loo...

Variable Assignment variable_name = value Use this syntax to store a piece of data in a variable. The variable name goes on the left, the equals sign is the assignment operator, and the data value goes on the right. Text Data (Strings) variable_name = "some text inside quotes" When your data is text, like a name or a message, you must always put it inside quotation marks. This tells the computer it's a 'string' of characters. Data Collection Pattern 1. Ask a Question -> 2. Collect Data -> 3. Analyze Data This is the basic process for any data analysis project. First, know what you want to find out. Second, gather the information. Third, look for the answer in your information.