Yesterday I wrote a post: Ten Question Litmus Test for Professional SEOs. Today, as promised, I'm providing my answers to these questions. Note that these aren't the only way(s) to answer correctly, as some of the questions are more open-ended. In the answers, you'll also see citations to sources for the answers.

1. Which is more likely to have a positive impact on a page's search engine rankings and why - 10 links from 1 website or 1 link each from 10 different websites?
   _
   All other things being equal, there appears to be a very strong correlation between higher rankings and a diversity of linking domains. Hence, earning 10 links from 10 unique sites should provide greater benefit. My opinion is that Google rewards this type of linking because diversity indicates both broad popularity/importance and greater editorial citation vs. a single site (possibly one which has a relationship with the linked site). The larger quantity of linking domains is also a far greater barrier for marketers and businesses to earn vs. the single site's links.
   _
   (References: Correlation of Rankings, All Links are Not Created Equal)
   _
2. Explain the difference between the following items and how the search engines treat them - 301 response code, 302 response code, canonical URL tag and meta refresh.
   _
   A 301 redirect tells browsers and search engines that a page has been permanently redirected to a new URL. A 302 redirect indicates a temporary redirection that will change again or revert back in the future. Search engines such as Google and Bing interpret a 301 redirect by passing the link equity and ranking metrics from the 301'd URL to the target page. 302 redirects do not always receive this treatment (though exceptions exist) and may show in the search results with the original URL/snippet even after the 302 redirect is in place.
   _
   The Canonical URL tag is a < link rel> item in the header of a document that serves as a suggestion to search engines, indicating the "original" or "canonical" version of that page's content. It is intended to tell engines which URL is suitable for indexing when multiple pages contain the same or very similar content.
   _
   The meta refresh is a directive in the header of a document indicating that, after a certain quantity of time is passed, the browser should redirect to a new location (or reload the page). Search engines appear to treat most short meta refreshes (a few seconds in length) as permanent redirects, passing the link equity and ranking metrics to the target page (they also claim to do this 100% of the time for meta refreshes marked with "0" seconds of delay). Longer meta refreshes may be indexed as normal.
   _
   (References: SEO Advice: 302 Redirects, Canonical URL Tags, Google + Yahoo! w/ Meta Refreshes)
   _
3. How can the meta robots tag impact how search engines crawl, index and display content on a web page?
   _
   The meta robots tag can be used to specify whether a page is included in a search engine's public index (for display in results), whether links on the page are followed vs. nofollowed and the display of the snippet (removing the description and/or excluding titles/descriptions from the Open Directory Project or Yahoo! Directory for example). The tag can also be used to prevent a cached version of the page being available via the search results.
   _
   (References: Meta Robots Tag 101)
   _
4. Who are the top 2 search engines (as ranked by share of queries) in the following countries - the United States, United Kingdom, Russia and China?
   _
   In the United States, it's either Google & Bing or Google & YOUTube (though the latter is technically owned by Google and thus, could be considered a single entity. It's also true that YOUTube is a specialized site exclusively for video content, and thus may not "count" - this argument is often made in comparison to Twitter searches, many of which come through APIs). The UK matches the US on this front. In China, #1 is Baidu and Google is #2. In Russia, Yandex is #1 and Google is #2 (BTW, Yandex's English language results are pretty darn good, and have that nice, early Google minimalist feel to them).
   _
   (References: October 2010 US Search Engine Rankings, Hitwise UK Top Engines, iResearch data for China via Bloomberg, From Russia w/ Search Love)
   _
5. Name at least 3 elements critical to ranking well in Google Local/Maps/Places search.
   _
   Any of the following would be reasonable answers - registration/verification with Google Local/Places; listing presence & consistency in Google Places sources; ratings and reviews from Google Places users; proximity  to centroid and match on local phone number/address; listing prominence in Google Places sources (e.g. Yelp, Citysearch, Urbanspoon, Dexknows, etc.), listings/references from sources that feature in "more about this place" (typically from local coverage websites); business listing title/name/domain name.
   _
   (References: Local Ranking Factors, Ratings the New Reviews, Google Places Guidelines)
   _
6. What aspects of social media marketing have a positive impact on search engine rankings (apart from the value of direct links from the social sites)?
   _
   Social media is a form of awareness marketing and branding, which can bring a wide variety of search engine ranking benefits. The most obvious and direct is the potential for creation of links and references to the sites/pages that garner traffic and attention through social media. Another powerful influence is the use of social results directly in SERPs as seen by Google & Bing's integrations with Twitter (and Bing's integration with Facebook). Google also has connections, often via Gmail and other services to "results from my social circle" which can bring results to page 1 that otherwise wouldn't appear). There's also indications that tweets, in particular, may be directly influencing rankings and being treated as links, particularly for queries that call the QDF algorithm. Finally, brand associations and mentions may be mined by the engines from social sources and used in brand entities or co-citation algorithms to help a site/page be seen as more relevant or related to particular keywords and more "important" or "popular."
   _
   (References: Use Twitter to Rank in 5 Minutes, Google's Tweet Ranking Algorithm, Facebook + Bing's Plans to Make Search Social, Google Social Circle Goes Live)
   _
7. List 5 tags/locations on a page where employing a target keyword can have a positive effect on search engine rankings.
   _
   Any of the following would be reasonable answers: Title element, domain name, subdomain, URL string, body element, alt attribute, bold/strong tag.
   _
   (References: Perfecting KW Targeting + On-Page Optimization, Correlation of Google/Bing Rankings, Explaining Google's Algorithm w/ Math) 
   _
8. Describe the distribution of search query demand and what is meant by the "fat head" and "long tail."
   _
   Billions of searches are performed each week, but the vast majority of these (~70%) are query terms/phrases that are searched for less than 10 times per month. This distribution of demand is represented by a chart with a trailing line called the "long tail" (as coined by Chris Andersen of Wired). The head of this curve, where the queries are searched thousands-millions of times each month (very popular terms) is called the "fat head."
   _
   
   _
   (References: Hitwise Blog, Illustrating the Long Tail)
   _
9. Name 6 tools/sources that will display a list of external URLs that link to a webpage.
   _
   Any of the following sources would be acceptable: Google Webmaster Tools, Bing Webmaster Tools, Google Link Command (despite its shoddiness), Yahoo! Site Explorer, Yahoo! Link Commands (only available via non-Bing powered Yahoo!s), SEOmoz Linkscape, Majestic SEO, Blekko, Exalead, Google Blog Search, Alexa, or a site's own web analytics/log files.
   _
   (NOTE: Although there are many other tools in the SEO realm that contain link data, all of them (to my knowledge) are powered by one or more of the above sources.)
   _
10. What are some ways to positively influence the ratio of pages a search engine will crawl and index on a website?
    _
    There are a large number of potential ways to answer this question, so experienced SEOs will have to use their judgement about the answers given by others, but here are a few of the most obvious/sensible ones:
    _
    A) Reduce the quantity of low quality, low value and/or low unique-content pages.
    B) Add and verify an XML Sitemap to send URL information to the engines.
    C) Produce RSS feeds of pages/sections that frequently update with new content and use ping services to alert engines of changes/additions. D) Reduce the click-depth required to reach pages on the site.
    E) Eliminate confusing navigation and architecture such as high quantities of pagination, large numbers of faceted navigation or multiple versions of categorization/organization hierarchies.
    F) Reduce or eliminate duplicate content (or leverage solutions such as rel=canonical tags).
    G) Earn more links (or tweets possibly) to pages that are being passed over for crawling/indexing.
    _
    (References: Diagrams for Solving Crawl Priority, An Illustrated Guide to Matt Cutts Comments on Crawling + Indexation, Testing How Crawl Priority Works, Google's Indexation Cap, Crawling + Indexing: Not as Simple as Just In or Out, Solving Indexation Problems)
    _
11. BONUS! Describe the concept of topic modeling and how modern search engines might use it to improve the quality of their results.
    _
    Topic modeling is a way for search engines to mathematically resolve the relationships between words and phrases and help determine if a set of content is relevant to a query. These systems typically leverage a vector space model in which the degree of "related-ness" is represented with an angle or "cosine similarity" - smaller angles are more similar while larger ones are further away. Many tens or hundreds of thousands of dimensions may be necessary to accurately represent a corpus' collection of "topics" and the words/phrases that are related. Specific algorithms like LDA, LSI, LSA, pLSI, etc. are all forms of implementation of topic modeling.
    _
    (References: Google Tech Talk: Topic Modeling, Topic + Keyword Re-Ranking for LDA-Based Topic Modeling, LDA + Google's Rankings)
    _

Eventually, we'll be replacing our old SEO Expert Quiz with something more like this. I also saw a number of requests for certification from SEOmoz - it's something we've talked about, but had lots of concerns with (structure, logistics, policing, liability, etc.), but I'd love to hear your thoughts on this - is it a service you'd like to see from us? Is MarketMotive or another vendor doing a solid job here already?