Discrete Vs Continuous Quiz

The dog weighs 46.6 kg is an example of continuous data because weight is a measurable quantity that can take on any value within a certain range (in this case, the weight of the dog can be any value greater than 0 kg). In contrast, the other statements provide categorical or discrete data, as they describe characteristics of the dog that can only have specific values (four legs, one tail, two ears).

A discrete variable represents countable, distinct values, such as the number of students in a classroom. In this case, you can't have a fraction or a non-integer value for the number of students; it's always a whole number. The other options are continuous variables because they can take on a wide range of values, including fractions or decimals.

The correct answer is "Paul has three sisters." This is discrete data because it represents a countable and distinct value. The number of sisters Paul has is a whole number and cannot be divided into smaller units. In contrast, Paul's weight, height, and jumping height are continuous data because they can take on any value within a certain range and can be measured in smaller units.

The time it takes for a computer program to execute a task can be a continuous variable. It can take on a wide range of values, including fractions or decimals. Unlike discrete variables, which represent distinct, countable values, continuous variables can take on any value within a range.

The average size of the coconut grown by a tree is an example of continuous data because it can take any value within a range and can be measured with a high degree of precision. Continuous data are numerical data that can be divided into smaller increments and can include decimals and fractions, which is characteristic of measurements like size, weight, and volume.

Continuous data refers to data that can take on any value within a specific range. It is not limited to specific values or categories. The term "measured" implies that continuous data can be quantitatively measured, such as temperature, height, or weight. On the other hand, counting is more suitable for discrete data, where values can only be whole numbers or specific categories. Therefore, the correct answer is "Measured" because continuous data can be measured rather than counted.

The weight of a watermelon as measured each week is NOT discrete data because it can take on any value within a continuous range. Discrete data consists of distinct and separate values, such as the number of students attending a class or the number of cars a company sells each day, which can only be whole numbers.

Daily rainfall is an example of continuous data because it can take on any value within a certain range. It is measured on a continuous scale, such as millimeters or inches, and can have decimal values. Unlike discrete data, which can only take on specific values, daily rainfall can vary continuously and is not limited to distinct categories or intervals. Therefore, it is considered continuous data.

Bikes manufactured in a factory each day is not continuous data because it represents a count or a whole number value. Continuous data refers to measurements that can take any value within a given range, such as a person's weight or the volume of water in the Pacific Ocean. However, the number of bikes manufactured each day is discrete data, as it can only take specific integer values. Therefore, the correct answer is "Bikes manufactured in a factory each day".

Discrete data consists of distinct, separate values, often integers, with no values in between. Examples include the number of students in a class or the number of cars in a parking lot. Continuous data, on the other hand, can take on any value within a range, including fractional and decimal values. Examples include height, weight, and temperature.

Continuous data refers to data that can take on any value within a certain range. In the context of the question, the distance that a cyclist rides each day can vary and can take on any value within a certain range, such as 10 km, 15.5 km, or 20.3 km. Therefore, it is considered continuous data.

Discrete data refers to data that can only take specific values, typically whole numbers, and is countable. For example, the number of students in a class or the number of cars in a parking lot are examples of discrete data. Discrete data cannot be measured in the way continuous data can, such as height or weight, which can take any value within a range.

The number of people waiting at a bus stop is a discrete variable because it can only take on whole number values (e.g., 0, 1, 2, 3, etc.). You can't have a fraction or a non-integer value for the number of people waiting. Discrete variables represent distinct, separate values and are appropriate for counting, while continuous variables can take on any value within a range.

The frequency of a cyclist riding over a few kilometers weekly is an example of discrete data. Discrete data consists of distinct, separate values, often counted in whole numbers or integers. In this case, you would count how many times the cyclist rides over a few kilometers each week, which results in specific, countable values. Continuous data, on the other hand, represents measurements that can take on any value within a certain range, such as temperature or time, and can include decimal values.

The combined tonnage of mail passing through the local postal center is continuous data. Continuous data can take any value within a given range and can be measured with a high level of precision, including fractions or decimals. In this case, the weight of the mail can vary continuously, making it a continuous data type. Discrete data, on the other hand, consists of distinct, separate values or categories with no values in between.