Name each level of measurement for which data can be qualitative.
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 57m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
1. Intro to Stats and Collecting Data
Levels of Measurement
Problem 1.2.20
Textbook Question
Determine the level of measurement of the data listed on the horizontal and vertical axes in the figure.

Verified step by step guidance1
Step 1: Understand the concept of levels of measurement. There are four levels of measurement in statistics: nominal, ordinal, interval, and ratio. Each level determines the type of data and the mathematical operations that can be performed.
Step 2: Analyze the data on the horizontal and vertical axes. The data consists of specific times (e.g., 8:00 A.M., 8:52 A.M., etc.). These times are numerical and can be ordered sequentially.
Step 3: Determine if the data has a meaningful zero point. Time data, as shown here, does not have an absolute zero point (e.g., 0 does not represent the absence of time). Therefore, it is not ratio-level data.
Step 4: Check if the intervals between the times are meaningful. For example, the difference between 8:00 A.M. and 8:52 A.M. is 52 minutes, and this difference is consistent across the dataset. This indicates that the data is at the interval level of measurement.
Step 5: Conclude that the level of measurement for the data listed on both axes is interval, as the times can be ordered, and the differences between them are meaningful, but there is no true zero point.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Levels of Measurement
Levels of measurement refer to the different ways in which data can be categorized and quantified. The four primary levels are nominal, ordinal, interval, and ratio. Each level has distinct characteristics that determine the type of statistical analysis that can be performed. Understanding these levels is crucial for accurately interpreting data and selecting appropriate statistical methods.
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Time as a Data Type
Time can be measured in various formats, such as hours and minutes, and is often treated as a continuous variable. In statistics, time data can be analyzed to identify patterns, trends, or intervals. The representation of time in the data provided suggests that it can be classified as either interval or ratio, depending on whether a true zero point exists, which is essential for determining the level of measurement.
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Types of Data
Interval vs. Ratio Measurement
Interval measurement involves data that can be ordered and has meaningful differences between values, but lacks a true zero point, such as temperature in Celsius. Ratio measurement, on the other hand, has all the properties of interval measurement, plus a true zero point, allowing for the comparison of absolute magnitudes. In the context of time, while it can be treated as interval data, it is often more accurately classified as ratio data due to the existence of a true zero (midnight).
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