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  2. T-Mobile US - Wikipedia

    en.wikipedia.org/wiki/T-Mobile_US

    T-Mobile stated that there are a small handful of users who abuse the tethering plan by altering device software and/or the use of an Android app that masks T-Mobile's ability monitoring whether data is on-smartphone, or through smartphone mobile hotspot (tethering) by mimicking all data as on-smartphone use, with some customers abusing the ...

  3. T-Mobile data breach - Wikipedia

    en.wikipedia.org/wiki/T-Mobile_data_breach

    T-Mobile US, Inc. is an American wireless network operator and is the second largest wireless carrier in the United States, with 127.5 million subscribers as of September 30, 2024. T-Mobile had previously suffered data breaches in 2009. 2015, 2017, 2018, 2019, and 2020. [2] [3]

  4. US reaches $31.5 million settlement with T-Mobile over data ...

    www.aol.com/news/us-reaches-31-5-million...

    The FCC said T-Mobile suffered data breaches in 2021, 2022 and 2023 that impacted millions of ... T-Mobile will pay a $15.75 million civil penalty and has agreed to spend another $15.75 million ...

  5. Data plan - Wikipedia

    en.wikipedia.org/wiki/Data_plan

    Unlimited data plans have seen a large increase in usage by consumers since their initial introduction by U.S. network T-Mobile.These plans, instead of setting an overall maximum for the user, have an amount set-up that, when surpassed, will slow the speed of the network for that user.

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  7. Persons using television - Wikipedia

    en.wikipedia.org/wiki/Persons_using_television

    The formula used to calculate PUT is similar to HUT (Houses Using Television). PUT = (Rating / Share) x 100 [ 6 ] Nielsen's formula for PUT is the number of persons viewing TV divided by the total persons universe i.e. the television rating divided by the total share of television in a particular demographic area. [ 7 ]

  8. Trimmed estimator - Wikipedia

    en.wikipedia.org/wiki/Trimmed_estimator

    The median is the most trimmed statistic (nominally 50%), as it discards all but the most central data, and equals the fully trimmed mean – or indeed fully trimmed mid-range, or (for odd-size data sets) the fully trimmed maximum or minimum. Likewise, no degree of trimming has any effect on the median – a trimmed median is the median ...

  9. Horvitz–Thompson estimator - Wikipedia

    en.wikipedia.org/wiki/Horvitz–Thompson_estimator

    In statistics, the Horvitz–Thompson estimator, named after Daniel G. Horvitz and Donovan J. Thompson, [1] is a method for estimating the total [2] and mean of a pseudo-population in a stratified sample by applying inverse probability weighting to account for the difference in the sampling distribution between the collected data and the target population.