Determine the level of measurement of the data listed on the horizontal and vertical axes in the figure.
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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 statistical operations that can be performed.
Step 2: Analyze the horizontal axis (Age). The data on the horizontal axis represents age groups (e.g., 'Under 3', '3–12', '13–17', '18+'). These are categories that are ordered, but the intervals between them are not necessarily equal. This suggests that the level of measurement is ordinal.
Step 3: Analyze the vertical axis (Percent). The data on the vertical axis represents percentages, which are numerical values that have a meaningful zero point and equal intervals. This suggests that the level of measurement is ratio.
Step 4: Combine the analysis. The horizontal axis (Age) is ordinal, and the vertical axis (Percent) is ratio. This distinction is important for interpreting the data and choosing appropriate statistical methods.
Step 5: Conclude the analysis. The level of measurement for the horizontal axis is ordinal, and the level of measurement for the vertical axis is ratio. This information helps in understanding the type of data and the statistical techniques that can be applied.
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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 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.
Difference in Proportions: Hypothesis Tests Example 1
Categorical Data
Categorical data represents characteristics or qualities that can be divided into distinct groups or categories. In the context of the bar graph, the age groups (Under 3, 3-12, 13-17, 18+) are examples of categorical data. This type of data is often analyzed using frequency counts or percentages, making it essential for understanding how different categories compare to one another.
A bar graph is a visual representation of categorical data, where each category is represented by a bar whose length corresponds to the value it represents. In this case, the height of each bar indicates the percentage of children in each age group participating in vacation planning. Interpreting bar graphs involves analyzing the relative heights of the bars to draw conclusions about the data being presented.