ENGINEERING DATA ANALYSIS LESSON 1 TYPES OF DATA

Summary

This video script delves into the realm of statistics, tracing its origins to 1749 and highlighting its evolution from state information to a broader analytical discipline. It defines statistics as the science and art of handling numerical data, encompassing collection, presentation, analysis, and interpretation. The script categorizes data into quantitative and qualitative types, further dividing them into continuous, discrete, attribute, and open data, with nominal and ordinal as subsets of attribute data. The importance of understanding these data types for research and analysis is emphasized.

Takeaways

• 📚 The history of statistics can be traced back to 1749, with the original meaning referring to information about states, and it has evolved to include both the collection and analysis of data.
• 🔍 Statistics is defined as the science and art of dealing with figures and facts, encompassing the collection, presentation, analysis, and interpretation of numerical data from various sources.
• 📈 Statistical data is a sequence of observations made on a sample from a population, and can be either quantitative or qualitative, serving as the foundation for further measurement and analysis.
• 📊 Quantitative data is measured by values or counts and is expressed as numbers, while qualitative data is non-numerical and characterized by descriptions or observations.
• 📉 Continuous data, also known as variable data, can take the form of decimals or continuous values, such as height measurements that can have infinite precision.
• 🏠 Discrete data, on the other hand, is data that is represented as whole numbers and cannot be divided into smaller units, like family size or class enrollment.
• 👕 Attribute data is countable and can be recorded for analysis, such as the size of a t-shirt, categorized as small, medium, large, etc.
• 🌐 Open data is qualitative and allows for a wide range of responses without a specific set of values, such as personal opinions or predictions about the future.
• 👥 Nominal data is used to categorize without implying an order, such as gender, race, or political affiliation, where the categories are distinct and not ranked.
• 🏅 Ordinal data indicates a ranking or order among categories, such as levels of awareness or skill levels, where there is a clear hierarchy.
• 📝 The process of statistics involves the collection of data, followed by its representation, analysis, and interpretation, which are key steps in understanding and applying statistical concepts.

Q & A

When is the history of statistics said to have started?

The history of statistics is said to have started around 1749.

What does the original meaning of 'statistics' refer to?

In early times, the original meaning of 'statistics' was restricted to information about the states.

How has the meaning of 'statistics' evolved over time?

Over time, the meaning of 'statistics' has evolved to include not only the collection of information about states but also analytical work requiring statistical data.

What is the formal definition of statistics?

The formal definition of statistics is the science and art of dealing with figures and facts.

What are the four main components of the process of statistics?

The four main components of the process of statistics are the collection, representation, analysis, and interpretation of numerical data.

What is considered as statistical data?

Statistical data are a sequence of observations made on a set of objects included in the sample drawn from a population, or it can be defined as quantitative or qualitative values of a variable.

What are the two main classifications of data?

The two main classifications of data are quantitative and qualitative.

How is quantitative data defined?

Quantitative data is defined as data that measures values or counts and is expressed as numbers.

What is the difference between continuous and discrete data?

Continuous data, also known as variable data, can take the form of decimals or continuous values of varying degrees of precision. Discrete data, on the other hand, cannot be represented as decimals and are represented as whole numbers.

What are the two types of qualitative data?

The two types of qualitative data are attribute data and open data. Attribute data can be counted for recording and analysis, while open data is not given a specific value and can have a wide range of responses.

How are attribute data further subdivided?

Attribute data is further subdivided into nominal and ordinal data. Nominal data allows making statements only of quality or difference, while ordinal data has a rank or order.