MarinStatsLectures-R Programming & Statistics YouTube Channel Earnings Report & Research

To answer how much does MarinStatsLectures-R Programming & Statistics make, Branzly runs the channel's estimated 1.6K monthly views through the same ad revenue calculator used across the site: a Education RPM of $2.7-$6.8 from 2026 niche benchmarks, with the headline figure taken at the middle of that range ($4.8), the same RPM used in the home page calculator. That puts MarinStatsLectures-R Programming & Statistics YouTube ad revenue at roughly $4 to $11 per month, or $51 to $128 per year from AdSense alone.

RPM is what the channel actually keeps per 1,000 views after YouTube's 45% revenue share, unfilled ad inventory and ad blockers, which is why these MarinStatsLectures-R Programming & Statistics earnings figures sit far below the advertiser-side CPM quotes you may see elsewhere. Views from Tier 1 countries such as the United States, United Kingdom, Canada and Australia pay the most, while Shorts views pay a fraction of long-form RPM.

On top of ad revenue, we assume one integrated-mention sponsorship per month priced on 74.7K average views per video at a Education cost-per-view rate of $0.01 with a 1.2× niche multiplier — the identical model in our sponsorship calculator. That suggests a MarinStatsLectures-R Programming & Statistics sponsored video is worth about $903 to $1,806, with a fair midpoint near $1,290.

Sponsorship pricing follows views and engagement, not subscriber count, so a large channel with a quiet video is still only paid for the views that video earns. Brands asking "how much does it cost to sponsor MarinStatsLectures-R Programming & Statistics?" should expect dedicated videos to cost two to three times an integrated mention.

Channel-level deals work differently again. A retainer is an ongoing fee for a set of deliverables each month, not the sum of every slot the channel could sell, so pricing follows published size bands. With 171.0K subscribers, MarinStatsLectures-R Programming & Statistics sits in the Mid-tier (100K-500K subs) band, where retainers typically run $4,000 to $15,000 a month. Niche demand, engagement, cadence across 1 uploads a month and how much of the audience watches each upload decide where in that band a deal lands. Spread back across uploads, that adds about $10,492 of value to each video.

Put simply, MarinStatsLectures-R Programming & Statistics YouTube earnings are estimated at roughly $8,252 to $16,506 per month when ad revenue, one sponsored integrated mention and a retainer are combined, or about $99,022 to $198.1K per year. Channels that publish more sponsored videos, sell merchandise or courses, run memberships, or earn affiliate commissions typically make more than this range.

Net worth estimates for YouTubers like MarinStatsLectures-R Programming & Statistics usually start from several years of this yearly income, minus taxes, team costs and production spend. Treat any MarinStatsLectures-R Programming & Statistics net worth figure as a planning range, not a disclosed number.

MarinStatsLectures-R Programming & Statistics (@marinstatlectures) is a education YouTube channel that has published 269 videos and accumulated 20,086,703 lifetime views from an audience of 171,000 subscribers. The channel was created in July 2013, which makes it roughly 13 years and 4 months old, and it continues to publish content for viewers interested in education topics. In the creator's own words: "These R Programming and Statistics tutorials are originally created for Master's and PhD students at UBC by Professor Mike Marin and are now available to public.These videos provide a comprehensive and completely free set of tutorials for introductory and intermediate concepts in Statistics and Statistics with R. Our team: Professor Mike Marin is the content creator for these video tutorials an" Branzly analyses MarinStatsLectures-R Programming & Statistics using public YouTube data so creators, brands and media buyers can understand the channel's size, output and likely earning power before they reach out, benchmark against it, or plan a collaboration.

MarinStatsLectures-R Programming & Statistics has been on YouTube for approximately 13 years and 4 months, starting in July 2013. Across that period the channel has averaged around 21 uploads per year, which gives a useful signal about publishing consistency: channels that maintain a steady cadence typically build stronger session watch time and more predictable sponsorship inventory than channels that upload in bursts. Longevity also matters for advertisers, because an established back catalogue keeps generating views long after each video's launch week. With 269 videos in the library, MarinStatsLectures-R Programming & Statistics earns a meaningful share of its monthly views from older content rather than from new uploads alone, and that evergreen tail is one reason estimated revenue for education channels can stay stable between releases.

MarinStatsLectures-R Programming & Statistics currently has 171,000 subscribers, a figure that places the channel in the established mid-tier tier of YouTube creators. Total channel views stand at 20,086,703, and average views per video sit at approximately 74,672. The ratio of lifetime views to subscribers is about 117.5 views for every subscriber, which indicates a strong reach beyond the subscribed audience, typically driven by search, suggested video placements or Shorts distribution. Branzly estimates recent activity at roughly 1,563 views per month based on the channel's most recent uploads and publishing history, which is the number our ad revenue calculator uses to model earnings.

The most-watched long-form video currently visible for MarinStatsLectures-R Programming & Statistics is "6.2 Logistic Regression Models in R" with 47,454 views. On the Shorts side, "8.4 Effect Modification: Stratifying vs. Modelling It With Interaction Term in R" leads with 5,583 views. Top-performing titles are worth studying because they reveal which hooks, formats and topics the algorithm rewards for this audience. For brands, they also show the realistic ceiling of a sponsored placement: a dedicated integration on a channel of this size will usually land somewhere between the average video performance of 74,672 views and the outliers shown above.

Based on an estimated 1,563 monthly views and typical education CPM ranges, MarinStatsLectures-R Programming & Statistics could earn roughly $4 to $10 per month from YouTube ad revenue, or approximately $50 to $127 per year. These figures reflect the AdSense share only. Most channels of this size also earn from brand sponsorships, affiliate links, memberships, merchandise and product sales, so total creator income is commonly several times the advertising estimate. Sponsorship value is usually priced per view rather than per thousand impressions, and education audiences typically command mid-range rates because of advertiser demand in that vertical.

Branzly classifies MarinStatsLectures-R Programming & Statistics under the Education category using the channel's description, keywords, topic signals and the language of its best-performing uploads. Category matters more than raw subscriber count when estimating revenue: a education channel attracts a specific set of advertisers, and CPMs vary widely between verticals such as finance, software, education, gaming and entertainment. The channel lists CA as its primary country, which further shapes its CPM because advertiser spend differs sharply between geographies. Public channel keywords include best r course for beginners, r for data science, r programming for data science, Statistics course for beginners, statistics tutorial for beginners, statistics course for data science, r course for beginners, ap statistics, which supports this classification. Use the Branzly ad revenue, sponsorship and financial freedom calculators to model how a channel like MarinStatsLectures-R Programming & Statistics converts views into monthly income, sponsorship pricing and long-term wealth.

Every figure on this page comes from the public YouTube Data API, refreshed each time MarinStatsLectures-R Programming & Statistics is searched on Branzly. Subscriber counts, view counts and video counts are reported directly by YouTube. Monthly views are an estimate: YouTube does not publish per-month analytics for channels you do not own, so Branzly reconstructs recent performance from the views of the channel's latest uploads, falling back to lifetime views divided by channel age when recent data is sparse. Revenue ranges are modelled estimates, not disclosed earnings, and actual payouts depend on monetisation status, watch time, ad formats, seasonality, audience geography and YouTube's revenue share. Nothing on this page is financial advice, and Branzly is not affiliated with or endorsed by MarinStatsLectures-R Programming & Statistics or YouTube.

Education channels like MarinStatsLectures-R Programming & Statistics sit in the Education RPM bracket. Advertisers pay more for audiences that buy — finance, business and tech pay the highest rates, while entertainment, gaming and music rely on huge view volume. Seasonality matters too: Q4 ad rates commonly run 30–50% higher than January.

Every figure on this MarinStatsLectures-R Programming & Statistics channel earnings report comes from public YouTube Data API statistics — subscribers, lifetime views, video count and recent upload performance — refreshed when the report is opened. Estimates are modelled, not disclosed income, and not financial advice. Want to test your own assumptions? Open the YouTube money calculator or browse brands that already sponsor similar creators in the sponsors directory.