Data Types
1. Explain quantitative variables.
Quantitative variables, also known as numerical or continuous variables, are types of variables that represent measurable quantities and can be expressed with numerical values.
2. Explain the two types of quantitative variables (discrete and continuous) and provide some examples.
- Discrete variables: A discrete variable is a type of quantitative variable that can only take on distinct and separate values.
- Examples: number of students in a class, number of days in a week.
- Continuous variables: A continuous variable is a type of quantitative variable that can take on an infinite number of values within a given range.
- Examples: height, weight, temperature, and time.
3. Explain categorical variables.
A categorical variable is a type of variable that represents groupings or labels, and its values typically belong to non-numeric groups or classes.
4. Explain the three types of categorical variables (binary, nominal and ordinal) and provide some examples.
- Binary variables: A binary variable is a type of categorical variable with only two possible categories or outcomes
- Examples: Gender (Male/Female), Coin Flip (Heads/Tails)
- Nominal variables: A nominal variable is a categorical variable without an inherent order or ranking among its categories. It represents distinct groups or labels.
- Examples: Colours (Red, Blue, Green), Types of Fruits (Apple, Orange, Pear)
- Ordinal variables: An ordinal variable is a categorical variable with distinct, ordered categories and the order is meaningful.
- Examples: Satisfaction levels (Good, Neutral, Bad), Performance ratings (Poor, Fair, Good, Excellent)
5. Explain explanatory and response variables.
- An explanatory variable (Independent variable) explains changes in another variable.
- A response variable (dependent variable) measures the result of a study, explained by the explanatory variable.
6. Explain control variables and their use-case.
Control variables are variables that are held constant throughout the experiment. The primary purpose of control variables is to isolate and identify the specific effect of the independent variable on the dependent variable.
7. Explain Nominal Data and provide some example(s).
- Explanation: Nominal data represents categories or labels with no inherent order or numerical value. It provides the least amount of information among the four levels.
- Examples: Gender (e.g., male, female), colours (e.g., red, blue, green), or categories like “Yes” and “No.”
8. Explain Ordinal and provide some example(s).
- Explanation: Ordinal data indicates order or ranking among categories, but the intervals between them are not equal or meaningful.
- Examples: Satisfaction levels (Good, Neutral, Bad)
9. Explain Interval Data and provide some example(s).
- Explanation: Interval data has equal intervals between values, but it lacks a true zero point.
- Examples: Temperature measures (Celsius ad Fahrenheit), IQ scores, years (2000,2010, 2020)
10. Explain Ratio Data and provide some example(s).
- Explanation: Ratio data has equal intervals between values, a true zero point, and meaningful ratios. It provides the most information among the four levels and supports arithmetic operations.
- Examples: Height, weight, age, income, or any measurement where a true zero point exists, indicating the absence of the measured attribute.
11. There are four measurement scales—Nominal, Ordinal, Interval, and Ratio. For each scale, indicate whether it allows the calculation of [Mode, Median, Mean, differences, addition, multiplication, and division].
| Application / Features | Nominal | Ordinal | Interval | Ratio |
|---|---|---|---|---|
| Mode | Yes | Yes | Yes | Yes |
| Median | No | Yes | Yes | Yes |
| Mean | No | No | Yes | Yes |
| Difference between variables | No | No | Yes | Yes |
| Addition & Subtraction of variables | No | No | Yes | Yes |
| Multiplication & Division of variables | No | No | No | Yes |
12. There are four measurement scales—Nominal, Ordinal, Interval, and Ratio. For each scale, indicate whether the scale exhibits [equal spacing, rank order, and an absolute zero] by answering yes or no for each characteristic.
| Application / Features | Nominal | Ordinal | Interval | Ratio |
|---|---|---|---|---|
| Equal Spacing | No | No | Yes | Yes |
| Rank Order | No | No | Yes | Yes |
| Absolute Zero | No | No | No | Yes |