Podcast
Questions and Answers
What is the primary characteristic that distinguishes ordinal data from nominal data?
What is the primary characteristic that distinguishes ordinal data from nominal data?
- Ordinal data has a defined order or ranking, while nominal data does not. (correct)
- Ordinal data is used in surveys and questionnaires, while nominal data is not.
- Ordinal data can be assigned numerical values, while nominal data cannot.
- Ordinal data is more common in finance and economics than nominal data.
Which of the following is an example of continuous data?
Which of the following is an example of continuous data?
- The number of apples in a basket
- The number of cars in a parking lot
- The temperature of a room (correct)
- The number of students in a class
Which of the following is NOT an example of ordinal data?
Which of the following is NOT an example of ordinal data?
- Customer satisfaction ratings on a scale of 1 to 5
- Types of cars (sedan, SUV, hatchback) (correct)
- Letter grades in an exam (A, B, C, D, etc.)
- Ranking of athletes in a competition
Why are numerical values associated with some categorical data, like birthdate or postcode, not considered truly quantitative?
Why are numerical values associated with some categorical data, like birthdate or postcode, not considered truly quantitative?
Which type of data is best represented by a bar graph?
Which type of data is best represented by a bar graph?
Which of these examples best illustrates nominal data?
Which of these examples best illustrates nominal data?
Which of the following is an example of discrete data?
Which of the following is an example of discrete data?
What is the difference between nominal and ordinal data, in terms of their ability to be used in mathematical operations?
What is the difference between nominal and ordinal data, in terms of their ability to be used in mathematical operations?
What is the primary difference between quantitative and qualitative data?
What is the primary difference between quantitative and qualitative data?
Which of the following is an example of qualitative data?
Which of the following is an example of qualitative data?
Which type of data is best represented by a pie chart?
Which type of data is best represented by a pie chart?
Which of the following data sets is most likely to be continuous?
Which of the following data sets is most likely to be continuous?
What is the correct classification of data used to describe the number of people who voted in an election?
What is the correct classification of data used to describe the number of people who voted in an election?
Flashcards
Nominal Data
Nominal Data
Data that can be categorized but doesn't have a natural order. The categories are distinct and their values are not numerically related.
Ordinal Data
Ordinal Data
Data that can be categorized and has a natural order. The categories have a meaningful sequence. For example, low, medium, high, but you can't perform arithmetic operations on them.
Qualitative Data
Qualitative Data
Information that describes qualities or characteristics rather than numerical values. Examples include gender, marital status, or color.
Numerical Values in Categorical Data
Numerical Values in Categorical Data
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Classification of Qualitative Data
Classification of Qualitative Data
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What is data?
What is data?
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What is quantitative data?
What is quantitative data?
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What is Discrete data?
What is Discrete data?
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What is Continuous data?
What is Continuous data?
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What is qualitative data?
What is qualitative data?
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Give some examples of quantitative data
Give some examples of quantitative data
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Give some examples of Discrete data
Give some examples of Discrete data
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Give some examples of Continuous data
Give some examples of Continuous data
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Study Notes
Types of Data
- Data is the Latin word for fact. It can be numbers, names, or labels.
- Not all data represented by numbers are numerical. For example, 1 = male, 2 = female are labels, not numerical data.
Learning Objective
- Identify different types of data. Data is essential context; it's useless without context.
Types of Data (Hierarchy)
- Data is categorized as either:
- Categorical (Qualitative): This type of data is descriptive, not numerical. Examples include gender, eye color, and names. Further subcategories exist:
- Normal Data
- Ordinal Data
- Numerical (Quantitative): This type of data is, well, numerical. Examples include height, weight, and test scores. Further subcategories exist:
- Discrete Data
- Continuous Data
- Categorical (Qualitative): This type of data is descriptive, not numerical. Examples include gender, eye color, and names. Further subcategories exist:
Quantitative Data
- Also known as numerical data. It represents numerical values (how much, how often, how many).
- Provides information about quantities of something.
- Can be classified into two types based on the data sets.
- Examples include height, length, size, weight, room temperature, scores, marks, and time.
Classification of Quantitative Data
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Discrete Data: Can only take discrete values. Things can be counted in whole numbers. Examples include the number of students in a class, the cost of a cell phone, the number of employees in a company, or the number of players in a competition.
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Continuous Data: Can be calculated. It has an infinite number of probable values within a specific range. Examples include temperature range, height of a person, speed of a vehicle, and time taken to finish a task.
Examples of Discrete Data
- Total number of students in class
- Cost of a cell phone
- Number of employees in a company
- Total number of players participating in a competition
Examples of Continuous Data
- Height of a person
- Speed of a vehicle
- Time taken to finish a task
- Market share price
Qualitative Data
- Also known as categorical data.
- Describes data that fits into categories. It is not numerical.
- Categorical information involves categorical variables.
- Examples include categorical variables like gender, hometown.
- These data can be in the form of audio, images, symbols, or text.
- Examples of qualitative data include hair color (blonde, red, brown, black), marital status (single, widowed, married), nationality (Filipino, Indian, German, American), and gender (male, female, other).
Classification of Qualitative Data
- Nominal Data: No order or ranking. Data values are just names, labels, or categories with no inherent numerical significance or order. Examples include colors (blue, red, green), and gender (male, female).
- Ordinal Data: Data is ranked or ordered in some way. Examples include letter grades (A, B, C, D), ranking of people in a competition (first, second, third) rankings of customer satisfaction on a scale of 1 to 10, or education level (higher, secondary, primary).
Examples of Nominal Data
- Colour of hair (blonde, red, brown, black)
- Marital status (single, widowed, married)
- Nationality (Filipino, Indian, German, American)
- Gender (male, female, other)
Examples of Ordinal Data
- Feedback, experience, or satisfaction on a scale of 1 to 10.
- Letter grades (A, B, C, D, etc.)
- Ranking of people in a competition (First, Second, Third, etc.)
- Education level (Higher, Secondary, Primary).
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