ISEE Lower Level Quantitative Reasoning Flashcards: Tables And Averages

What this deck covers

This deck focuses on Tables And Averages, giving you a quick way to review the definitions, rules, and examples that matter most for ISEE Lower Level Quantitative Reasoning.

How to use these flashcards

Work through these flashcards in short sessions. Try to answer each prompt before flipping the card, then revisit any cards you miss until the explanation feels automatic.

Flashcard 1: Which variable is averageable: number of pets or type of pet (dog, cat)?

Answer: Number of pets. Number of pets is a quantitative count appropriate for averaging, whereas type of pet is categorical.

Flashcard 2: What is the mean of the values $15, 18, 12$?

Answer: $15$. The mean is found by summing the values and dividing by the count, giving rac{15+18+12}{3}=15.

Flashcard 3: A table column contains values $2.5, 3.0, 2.0$ with unit kilograms. Is it averageable?

Answer: Yes; it is numerical with consistent units (kilograms). The values are numerical and share the same unit, allowing them to be summed and divided for a meaningful average.

Flashcard 4: Identify the averageable variable: colors (red, blue) or heights (inches).

Answer: Heights (inches). Heights are quantitative measurements in consistent units suitable for averaging, whereas colors are categorical and cannot be meaningfully averaged.

Flashcard 5: Which variable is averageable: number of books read or book titles?

Answer: Number of books read. Number of books read is a quantitative count suitable for averaging, whereas book titles are categorical labels.

Flashcard 6: A table column mixes $3$ inches, $10$ centimeters, and $0.2$ meters. Can it be averaged as written?

Answer: No; units are mixed, so the values must be converted first. Mixed units prevent direct comparability, requiring conversion to a common unit before averaging can be meaningful.

Flashcard 7: What is required for a table column to be averageable: equal units or mixed units?

Answer: Equal units; mixed units cannot be averaged meaningfully. Consistent units ensure that the values are comparable, enabling a meaningful average, whereas mixed units lead to inconsistent and invalid results.

Flashcard 8: In a table, which is averageable: time (minutes) or winner name?

Answer: Time (minutes). Time in minutes is a numerical measurement with consistent units that can be averaged, unlike winner names which are categorical.

Flashcard 9: What type of variable in a table can be averaged: categorical labels or numerical measurements?

Answer: Numerical measurements can be averaged; categorical labels cannot. Numerical measurements represent quantifiable data allowing arithmetic operations like averaging, while categorical labels are qualitative and do not support meaningful averages.

Flashcard 10: Which variable is averageable: page numbers read per day or book genres?

Answer: Page numbers read per day. Page numbers read per day are numerical data appropriate for averaging, unlike book genres which are categorical.

Flashcard 11: What is the mean of the values $6, 9$?

Answer: $7.5$. The mean is computed by summing the values and dividing by the count, giving rac{6+9}{2}=7.5.

Flashcard 12: Which column is averageable: Student names or scores (points)?

Answer: Scores (points). Scores are numerical values with consistent units that can be summed and divided, unlike student names which are categorical labels.

Flashcard 13: A table lists ranks $1, 2, 3, 4$ for finish order. Can rank be averaged meaningfully?

Answer: No; ranks are ordinal and the mean rank is usually not meaningful. Ranks are ordinal data where intervals between values are not equal, making their average statistically invalid or uninformative.

Flashcard 14: Which column is averageable: ages (years) or favorite sport?

Answer: Ages (years). Ages in years are numerical measurements with consistent units that can be averaged, unlike favorite sport which is categorical.

Flashcard 15: Which variable is averageable: distances (miles) or cities visited?

Answer: Distances (miles). Distances in miles are numerical with consistent units suitable for averaging, unlike cities visited which are categorical.

Flashcard 16: What is the mean of the values $10, 12, 8, 10$?

Answer: $10$. The mean is found by adding the values and dividing by the number of values, resulting in rac{10+12+8+10}{4}=10.

Flashcard 17: Which column is averageable: amount of money ($ dollars) or store names?

Answer: Amount of money (dollars). Amount of money in dollars is numerical with consistent units allowing averaging, unlike store names which are categorical.

Flashcard 18: What is the mean of the values $4, 4, 5, 7$?

Answer: $5$. The mean is determined by adding the values and dividing by their count, resulting in rac{4+4+5+7}{4}=5.

Flashcard 19: What is the mean of the values $1, 2, 2, 3, 2$?

Answer: $2$. The mean is calculated as the sum of the values divided by the number of values, yielding rac{1+2+2+3+2}{5}=2.

Flashcard 20: What is the mean of a variable with values $3, 5, 7$?

Answer: $5$. The mean is calculated by summing the numerical values and dividing by the count, yielding rac{3+5+7}{3}=5.

Flashcard 21: Which column is averageable: ID numbers used only as labels or test scores?

Answer: Test scores; label-only ID numbers are not averageable. Test scores are numerical data suitable for averaging, while ID numbers as labels are nominal and lack quantitative meaning.

Flashcard 22: Identify the averageable variable: monthly rainfall (inches) or month names.

Answer: Monthly rainfall (inches). Monthly rainfall in inches is a quantitative measurement with consistent units suitable for averaging, whereas month names are categorical.

Flashcard 23: Which variable is averageable: number of goals or team names?

Answer: Number of goals. Number of goals is a quantitative count suitable for averaging, whereas team names are categorical labels.

Flashcard 24: Identify the averageable variable: shoe sizes or shoe brands.

Answer: Shoe sizes. Shoe sizes are numerical values that can be averaged meaningfully, unlike shoe brands which are categorical.