Vast Majority Of Us Would Prefer A Thicker Smartphone If It Meant A Better Battery

Americans don't want thinner phones. At least, not if that means shorter battery life.

Americans don't want thinner phones. At least, not if that means shorter battery life.

A new HuffPost/YouGov poll finds that an overwhelming majority -- 73 percent -- of adults polled would prefer a thicker phone with longer battery life to a thinner one with shorter life.

Only 12 percent said they'd prefer a thin phone with less battery life, while 15 percent said they weren't sure.

The results come one day after Samsung announced its new flagship Galaxy S6 phone, which is thinner and lighter than the Galaxy S5. It also has a smaller-capacity battery than the S5. Samsung, however, claims the new device is more efficient and should last longer than the old one, despite the weaker battery.

In a recent column for The Wall Street Journal, tech columnist Christopher Mims suggested it would take a brave phone maker to buck the trend of thinner smartphones in favor of longer-lasting batteries. If our survey is any indication, maybe it would just take a smart one.

Tell us what you think:

The HuffPost/YouGov poll consisted of 1,000 completed interviews, including 571 smartphone users, conducted Feb. 27-March 1 among U.S. adults using a sample selected from YouGov's opt-in online panel to match the demographics and other characteristics of the adult U.S. population.

The Huffington Post has teamed up with YouGov to conduct daily opinion polls. You can learn more about this project and take part in YouGov's nationally representative opinion polling. Data from all HuffPost/YouGov polls can be found here. More details on the poll's methodology are available here.

Most surveys report a margin of error that represents some, but not all, potential survey errors. YouGov's reports include a model-based margin of error, which rests on a specific set of statistical assumptions about the selected sample, rather than the standard methodology for random probability sampling. If these assumptions are wrong, the model-based margin of error may also be inaccurate. Click here for a more detailed explanation of the model-based margin of error.

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