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What Metric-dimension Combination Is Not Valid

Q: What metric-dimension combination is not valid?

A) Total Events / User TypeB) Sessions / SourceC) Avg. Time on Page / Device CategoryD) Sessions / Bounce rate

Correct Answer is D) Sessions / Bounce rate.

Explanation:

In Google Analytics, metrics and dimensions are two types of data that provide valuable insights into website performance and user behavior. Metrics are quantitative measurements, such as the number of sessions, page views, or conversions, while dimensions are attributes of user activity, such as the source or device used to access the site. However, not all metric-dimension combinations are valid, and it is essential to understand which combinations are not valid to ensure accurate data analysis and reporting.

The Google Analytics interface will not allow users to create an invalid combination of metrics and dimensions, so it is not possible to accidentally create an invalid combination within the interface. However, users can create custom reports, and they can use the Google Analytics Reporting API to access data programmatically. In these cases, it is essential to understand which metric-dimension combinations are not valid.

There are two main reasons why a metric-dimension combination may not be valid:

  1. Incompatible Data Types: The first reason why a metric-dimension combination may not be valid is that the data types of the metric and dimension are incompatible. For example, some metrics, such as bounce rate, are expressed as a percentage. It is not valid to combine a percentage metric with a dimension that is not compatible, such as a time-based dimension, like hour of the day or day of the week. Other metrics, such as page load time, are expressed as a duration. It is not valid to combine a duration metric with a dimension that is not compatible, such as a country or source.
  2. Sampling: The second reason why a metric-dimension combination may not be valid is sampling. When a report is based on a large dataset, Google Analytics may use sampling to reduce the amount of data that needs to be processed. When data is sampled, it means that only a portion of the data is used to generate the report. In some cases, certain metric-dimension combinations may not be valid when data is sampled. For example, if a report is based on a large dataset and includes both the “Hour of the Day” and “Device Category” dimensions, it is likely that the data will be sampled. In this case, the “Hour of the Day” dimension may not be valid because it is too granular to be accurately represented in a sampled report.
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It is essential to note that not all metric-dimension combinations are meaningful or useful. Just because a combination is valid does not necessarily mean that it will provide meaningful insights or actionable information. Users should always consider the context of their data analysis and focus on the combinations that are most relevant to their goals and objectives.

In conclusion, not all metric-dimension combinations are valid in Google Analytics, and it is essential to understand the reasons why certain combinations may not be valid. The two main reasons are incompatible data types and sampling. It is important to note that not all valid combinations are meaningful or useful, and users should always consider the context of their data analysis to ensure that they are focusing on the most relevant combinations. By understanding which metric-dimension combinations are valid and meaningful, users can gain valuable insights into website performance and user behavior.

Learn more on the official Google support website.

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