Question 1

Discrete data are inherently categorical.

Accepted Answer

Discrete data are data that can only take on certain values, and these values are typically whole numbers. Categorical data, on the other hand, are data that can be classified into different categories. Since discrete data can be classified into different categories, it is inherently categorical.

Question 2

Continuous data can be converted into discrete data, but discrete data cannot be converted into continuous data.

Accepted Answer

Continuous data can be divided into smaller units, while discrete data cannot.

Question 3

With nominal level data, some basic statistical comparison and crosstabulation are possible.

Accepted Answer

Nominal level data, which categorizes data without a natural order or ranking, allows for basic statistical comparisons such as frequency counts and mode, and crosstabulation to examine relationships between variables.

Question 4

Likert-type scales (strongly agree, agree, disagree, and strongly disagree) are interval level data.

Accepted Answer

Likert-type scales are considered ordinal level data because they represent ordered categories without a known consistent interval between each category.

Question 5

The only difference between interval level data and ratio level data is the existence of equal distance among attributes.

Accepted Answer

The main difference between interval level data and ratio level data is that ratio level data has a true zero point, indicating the absence of the quantity being measured, while interval level data does not have a true zero point.

Question 6

Bivariate statistics that analyze the relationship between two variables can determine their causality.

Accepted Answer

Bivariate statistics can analyze the relationship between two variables to determine correlation, but they cannot definitively establish causality. Causality requires further experimental or longitudinal studies to rule out other variables.

Question 7

In a situation when there is no exact median, it can be calculated by taking the average of the middle two numbers.

Accepted Answer

When there is an even number of observations in a dataset, the median is calculated by taking the average of the two middle numbers.

Question 8

Range is the difference between the highest score and the mean.

Accepted Answer

Range is the difference between the highest and lowest scores in a data set, not between the highest score and the mean.

Question 9

Range, variance, and standard deviation are measures of variability.

Accepted Answer

These statistical measures are used to describe the spread or dispersion of a set of data points. Range gives the difference between the highest and lowest values, variance measures the average squared deviation from the mean, and standard deviation is the square root of variance, indicating how much the data varies from the average.

Question 10

Which of the following is false regarding symbolic representations?

Accepted Answer

N typically represents the total number of elements in a population, not a sample. The sample size is usually denoted by n.

Question 11

__________ data are collected from categories; therefore, they have a set endpoint and are finite.

Accepted Answer

Discrete data are collected from categories and have a set endpoint, making them finite. This contrasts with continuous data, which can take any value within a range and are therefore infinite.

Question 12

A person's __________ is not an example of discrete data.

Accepted Answer

Height is a continuous variable, as it can take any value within a range and is not limited to distinct, separate values like discrete data.

Question 13

__________ data are not finite; therefore, they can be divided and broken down into smaller values such as 1.53.

Accepted Answer

Continuous data are not finite and can be divided into smaller values, unlike discrete data which are countable in a finite amount of time. Continuous data can take any value within a given range, such as measurements that include fractions or decimals.

Question 14

A person's __________ is not an example of continuous data?

Accepted Answer

Marital status is a categorical variable, not continuous. Continuous data can take any value within a range, such as weight, money, and grade point average, which can all vary in infinitely small amounts.

Question 15

Which of the following is false regarding nominal level data?

Accepted Answer

Calculating frequencies or percentages is possible and common with nominal level data, as these operations do not imply any inherent order or mathematical operation beyond counting and grouping.

Question 16

Which of the followings is false regarding ordinal level data?

Accepted Answer

All the statements about ordinal level data are true: they are rank-ordered categories (A), they are exhaustive and mutually exclusive (B), and they do not have equal distances between ranks (C), making none of the options false.

Question 17

Which of the following is an example of ordinal level data?

Accepted Answer

Likert-type scale data is an example of ordinal level data because it involves ranking or ordering of values (e.g., strongly agree, agree, neutral, disagree, strongly disagree) without indicating the exact differences between the ranks.

Question 18

Examples of __________ level data include GRE scores and IQ scores.

Accepted Answer

GRE scores and IQ scores are examples of interval level data because they are measured along a scale where each point is placed at equal distances from one another, but there is no true zero point.

Question 19

Which of the following characteristics must interval level data have?

Accepted Answer

Interval level data must have exhaustiveness, mutual exclusiveness, rank order, and equal distance between values, but it does not require a true zero point.

Question 20

Examples of __________ level data include weight, height, and enzyme activity that have a true zero as a starting point.

Accepted Answer

Ratio level data have a true zero point, allowing for the measurement of the absence of the quantity. Weight, height, and enzyme activity can all be measured from an absolute zero, making them examples of ratio level data.

Quiz 9: Elementary and Intermediate Quantitative Data Analysis