> The Bee Informed Partnership (http://beeinformed.org), in collaboration with the Apiary Inspectors of America (AIA) and the United States Department of Agriculture (USDA), is releasing preliminary results for the ninth annual national survey of honey bee colony losses. For the 2014/2015 winter season, a preliminary 6,128 beekeepers in the United States provided valid responses. Collectively, these beekeepers managed 398,247 colonies in October 2014, representing about 14.5% of the country’s estimated 2.74 million managed honey bee colonies

While I admire the work that Bee Informed Partnership is doing to try to assess and analyze the state of beekeeping in the USA today, there is a serious flaw in their methodology. Anyone who knows about surveys, knows about sampling skew. So far as I can see, there is no effort to correct for reporting bias, no effort to create a valid cross section. They have 14% reporting and they extrapolate. For example, if you cold call people to ask them questions you lose 90% right off the bat because they hang up. The remaining 10% who are willing to chat on the phone can hardly be said to represent the whole.

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Bias in Survey Sampling

In survey sampling, bias refers to the tendency of a sample statistic to systematically over- or under-estimate a population parameter.

Bias Due to Unrepresentative Samples

A good sample is representative. This means that each sample point represents the attributes of a known number of population elements.

Bias often occurs when the survey sample does not accurately represent the population. The bias that results from an unrepresentative sample is called selection bias. Some common examples of selection bias are described below.

Undercoverage. Undercoverage occurs when some members of the population are inadequately represented in the sample.

Nonresponse bias. Sometimes, individuals chosen for the sample are unwilling or unable to participate in the survey. Nonresponse bias is the bias that results when respondents differ in meaningful ways from nonrespondents. 

Voluntary response bias. Voluntary response bias occurs when sample members are self-selected volunteers, as in voluntary samples. An example would be call-in radio shows that solicit audience participation in surveys on controversial topics (abortion, affirmative action, gun control, etc.). The resulting sample tends to overrepresent individuals who have strong opinions.

Increasing the sample size tends to reduce the sampling error; that is, it makes the sample statistic less variable. However, increasing sample size does not affect survey bias. A large sample size cannot correct for the methodological problems (undercoverage, nonresponse bias, etc.) that produce survey bias. 

http://stattrek.com/survey-research/survey-bias.aspx

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