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Answers of Question What metric-dimension combination is not valid? is Sessions / Bounce rate, asked in Google Analytics Individual Qualification Exam. More About Google Analytics Individual QualificationGoogle Analytics Individual Qualification is given by Google and with Google Analytics Individual Qualification you can demonstrate your mastery of covers basic and advanced Google Analytics concepts. The Google Analytics Individual Qualification has 2 modules viz Google Analytics for Beginners and Advanced Google Analytics. One of the question asked in certification Exam is, What metric-dimension combination is not valid? You have to complete all course videos, modules, and assessments and receive a minimum score of 80% on each assessment to receive credit. Google Analytics Individual Qualification Certification will make you expert in Google Analytics, though which you can gain benefit in your business or career. Other Important Google Exam Links – Must visitYou should visit our few findings below for success in exam ServiceCentreList.com is providing the answer of questions asked in Google Analytics Individual Qualification exam. With these answers you will be able to score 100%+ exam and can get Google Analytics Individual Qualification. For that you need to just attempt all the questions mentioned for Google Analytics Individual Qualification. What metric-dimension combination is not valid?
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OverviewEvery report in Analytics is made up of dimensions and metrics. Dimensions are attributes of your data. For example, the dimension City indicates the city, for example, "Paris" or "New York", from which a session originates. The dimension Page indicates the URL of a page that is viewed. Metrics are quantitative measurements. The metric Sessions is the total number of sessions. The metric Pages/Session is the average number of pages viewed per session. The tables in most Analytics reports organize dimension values into rows, and metrics into columns. For example, this table shows one dimension (City) and two metrics (Sessions and Pages/Session).
In most Analytics reports, you can change the dimension and/or add a secondary dimension. For example, adding Browser as a secondary dimension to the above table would result in the following:
Valid dimension-metric combinationsNot every metric can be combined with every dimension. Each dimension and metric has a scope: user-level, session-level, or hit-level. In most cases, it only makes sense to combine dimensions and metrics that share the same scope. For example, Sessions is a session-based metric so it can only be used with session-level dimensions like Source or City. It would not be logical to combine Sessions with a hit-level dimension like Page. For a list of the valid dimension-metric pairs, use the Dimensions and Metrics Reference. How metrics are calculatedIn Analytics, user metrics are calculated in two basic ways:
The following diagram illustrates these two types of calculations with a simple example. On the left side, user data is calculated as an overview metric, while the same data is calculated via the New User dimension on the right side. In the Overview Report example, calculations for time on site are computed using the time difference between each user's initial session and the exit, with the sum of each session length averaged across three sessions. This number is based on a relatively simple calculation achieved by gathering time stamp data at the request level. In the New vs Returning Report example, averages are not computed for all sessions, but rather via the User Type dimension. By pairing the Time On Site metric with a dimension, you can analyze this metric via returning vs new users, where the calculations are modified by the requested dimension. The use of the dimension offers an insight into user behavior not provided in the overview report: it's clear that new users are spending more time on your site than returning users. Metrics calculation is also affected by stacking more than one dimension with a given metric. In both the preformatted and custom reports, you can use multiple dimensions together. For example, suppose you use both the User Type dimension and the Language dimension to analyze time on site for your website. In this case, the calculation for new versus returning users is the same, but when you drill down to view new users using the Language dimension, the calculation is further modified by the additional dimension. So, for example, your user breakdown might look like this, where the top site times are listed in order:
These numbers are based on an actual Analytics report. In this case, you can determine whether new or returning users stayed the longest, and by using an additional dimension, which languages in each of these categories resulted in the longest time on site. Attribution modelsBecause Analytics attempts to answer a variety of questions about user behavior, it uses different calculation types or attribution models to arrive at the data that you see in the reports. Think about each Analytics report as a response to a particular kind of user analysis question. Often, these questions fall into distinct categories:
For each of these major categories and the reports that they contain, Analytics uses a distinct attribution model. Because each attribution model is designed to calculate a known set of metrics, you might notice that some metrics—such as Pageviews—appear only in certain reports and not in others. This is due to the attribution model that is used for that report. The Analytics reports use three attribution models:
Per Request attributionThis attribution gives aggregate values for a single metric or for a metric/dimension pairing. This is the most common and simplest type of Analytics attribution, since values are determined from individual user GIF requests. Thus, for any given request, it is possible to look up a particular dimension and/or metric. Most dimension values are available at the request level and remain persistent either via the
Page Value attributionThe purpose of this attribution type is to answer the question: "How useful was my page in relation to a goal or revenue value?" This attribution model is used to determine the Page Value value for a page or set of pages. The following illustration shows a series of user pageviews in relationship to goals and purchases, such as what might occur on your site. Legend: P1 through P4 represent pages. The shopping bags indicates a receipt page, and the flag image indicates a goal.This attribution model is referred to as a "forward looking" attribution model, because it applies value to a page by looking forward to the goals and/or purchases that take place after the page was visited. The following table shows the value attributed to each page in this sequence.
This attribution model is not used in Goals or Ecommerce reports, since those reports do not display page URIs or titles in relation to ecommerce activities. Site Search AttributionThis attribution model allows the Site Search reports to display goal conversion rates and goal values per search term. This attribution model operates in a different fashion from Page Value attribution, since Goal value is attributed to the nearest search term leading up to the conversion, not after. The following diagram illustrates a sequence of internal site searches along with page views and purchases. Legend: P1 through P4 represent pages. The shopping bags indicates a receipt page, the search icon indicates a search for the terms "Shoes" and "Flowers." The flag image indicates a goal.Using this model, the search terms attributed to Goal 1 and the transactions are:
In this model, transactions or goals are attributed to the search term immediately preceding the goal or transaction. Was this helpful? How can we improve it? What metricExplanation: Sessions and Bounce Rate come under metrics. That's why “Sessions / Bounce rate” is not a valid metric-dimension combination.
Which of the following is not a valid dimension in Google Analytics?Explanation: Both Sessions and Bounce Rate come under metrics. You need to have 1 metric and 1 dimension to make a correct combination for any Google Analytics report. Whereas Session and Bounce rate come under metrics. That's why “Sessions / Bounce rate” can not be a valid metric-dimension combination.
What is metrics and dimension?Throughout most reports, metrics are the quantitative measurements of data and dimensions are the labels used to describe them—or, in even easier terms: metrics are always expressed by numbers (number values, %, $, time), while dimensions are expressed by non-numerical values.
Can we combine any metric with any dimension in a Google Analytics report?Not every metric can be combined with every dimension. Each dimension and metric has a scope: user-level, session-level, or hit-level. In most cases, it only makes sense to combine dimensions and metrics that share the same scope.
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