Classifying Data

The number of absent students is a discrete variable because it can only take on whole number values. It cannot be a fraction or a decimal.

The amount of rainfall during Hurricane Irene is a continuous variable because it can take on any value within a certain range. Rainfall can be measured in millimeters or inches, and there is no specific limit to the number of possible values it can have. It is not restricted to specific whole numbers or categories, making it a continuous variable.

The number of people in a survey that own a smartphone is a discrete variable because it can only take on certain specific values, such as 0, 1, 2, etc. It cannot take on any values in between, like 1.5 or 2.7.

The ratings of superior, above average, average, below average, and poor for a blind date can be classified as ordinal data. This is because the ratings have a clear order or ranking, with superior being the highest and poor being the lowest. However, the differences between the ratings are not necessarily equal or measurable, which is a characteristic of interval or ratio data. Therefore, the correct classification for this data is ordinal.

The concept of "time to complete assignment" can be measured in a continuous manner because it can take any value within a given range. It is not limited to specific intervals or discrete values. For example, it can take 5 minutes, 5.5 minutes, or even 5.5678 minutes. Therefore, it is considered a continuous variable.

The given statement is false. The SAT score does not directly measure a person's intelligence or overall smartness. It is a standardized test that assesses a student's knowledge and skills in specific subjects. Therefore, it is not accurate or fair to make a judgment about someone's intelligence based solely on their SAT score.

Ratio is the correct answer because distance traveled to school is a quantitative variable that has a meaningful zero point and can be measured on a continuous scale. It allows for meaningful comparisons and calculations, such as determining the ratio of one distance to another.

Why not ordinal? Does the ranking of lucky numbers mean anything?

The heights of a basketball team can be considered as a ratio level of measurement because they have a meaningful zero point (height cannot be negative or non-existent), the heights can be compared using ratios (one player's height can be expressed as a multiple of another player's height), and mathematical operations such as addition, subtraction, multiplication, and division can be performed on the data.

The term "birth year" refers to a specific point in time and can be measured on a continuous scale. It is not just a category or label (nominal), nor does it have a natural order or ranking (ordinal). Additionally, the difference between birth years is meaningful and can be measured (interval), but there is no true zero point (ratio). Therefore, "birth year" is best classified as an interval variable.

The SAT score is an example of an interval level of measurement. Interval data is measured on a scale where the intervals between values are equal and meaningful, but there is no true zero point. In the case of SAT scores, the intervals between scores are equal (e.g., the difference between a score of 1000 and 1100 is the same as the difference between 1500 and 1600), but a score of zero does not indicate the absence of the trait being measured.

The data items "Favorite song" and "Dinner choice" are nominal because they represent categories or labels rather than numerical values. They cannot be ranked or ordered in any meaningful way. On the other hand, "Price of dress" and "Number of people in limo" are not nominal as they represent numerical values that can be measured and compared.

Ordinal is the correct answer because shoe size is a categorical variable that can be ordered or ranked. In this case, shoe sizes have a specific order, such as 1, 2, 3, and so on, indicating a progression from smaller to larger sizes. However, the numerical difference between sizes is not meaningful, as it does not represent a consistent interval or ratio. Therefore, shoe size is an example of an ordinal variable.

Zip codes are generally ordered from northeast to southwest. For example, Amesbury, Ma is 01913; San Diego, Ca 92101

The data items "Number of passengers" and "Model year" can be considered discrete. The number of passengers can only take on specific whole number values, such as 0, 1, 2, etc. Similarly, the model year of a car can only take on specific discrete values, such as 2010, 2011, 2012, etc. On the other hand, "Gas mileage" and "Distance driving to school" are continuous variables, as they can take on any value within a certain range.