FDU POLL FINDS A THIRD OF ADULTS IN NJ CAN’T NAME GOVERNOR 

Fairleigh Dickinson University, Madison, New Jersey, June 17, 2019 – A third of all adults in the Garden State don’t know the name of the current governor. The most recent survey from the Fairleigh Dickinson University Poll finds that 67 percent say they know who the current governor is, with 33 percent who do not.

“Although politicians like to think everyone knows who they are, the good people of New Jersey are not unlike others across the country. A recent national surveyfinds that a third of all Americans can’t name their governor. So, as much as Governor Murphy may be disappointed, apparently he’s in good company,” said Krista Jenkins, professor of government and director of the FDU Poll.

Almost all of those who said they knew the governor’s name, actually did know it — or offered some version of the correct answer. Phil Murphy came to mind easily for many, though some offered only “Phil” or “Murphy.”  In the “let’s just give them credit because they were close enough” category were those who said William Murphy or Bill Murphy is the governor. And a handful (21 in total) said they knew who the governor is, and then offered the name of Murphy’s predecessor, Chris Christie.

Overall, Murphy’s approval is at 42 percent, with Democrats and Republicans predictably divided: Democrats approve by 61-16 and Republicans disapprove by 63-15.  Among those who can actually identify Governor Murphy by name, 43 percent approve of his job performance so far, while a third (36%) disapprove.

“It’s important to note that Governor Murphy remains under a 50 percent approval rate mainly because people don’t know him very well at all,” said Jenkins.  “On the bright side, this means he has a lot of potential to improve his ratings. On the pessimistic side, it means he’s just not connecting with voters.”

Methodology

The survey was conducted by live callers on both landlines and cellular phones between May 29 and June 4, 2019, with a scientifically selected random sample of 802 New Jersey adults, 18 or older. Persons without a telephone could not be included in the random selection process. Respondents within a household are selected by asking randomly for the youngest adult male or female currently available. If the named gender is not available, the youngest adult of the other gender is interviewed. The interview was conducted in English and included 318 adults reached on a landline phone and 484 adults reached on a cell phone, all acquired through random digit dialing.

The data were weighted to be representative of the non-institutionalized adult population of New Jersey. The weighting balanced sample demographics to target population parameters. The sample is balanced to match parameters for sex, age, education, race/ethnicity, region, and phone use. The sex, age, education, race/ethnicity and region parameters were derived from 2017 American Community Survey PUMS data. The phone use parameter was derived from estimates provided by the National Health Interview Survey Early Release Program.

Weighting was done in two stages. The first stage of weighting corrected for different probabilities of selection associated with the number of adults in each household and each respondent’s telephone usage patterns. This adjustment also accounts for the overlapping landline and cell sample frames and the relative sizes of each frame and each sample. This first stage weight was applied to the entire sample which included all adults.

The second stage of the weighting balanced sample demographics, by form, to match target population benchmarks. This weighting was accomplished using SPSSINC RAKE, an SPSS extension module that simultaneously balances the distributions of all variables using the GENLOG procedure. Weights were trimmed to prevent individual interviews from having too much influence on the final results. The use of these weights in statistical analysis ensures that the demographic characteristics of the sample closely approximate the demographic characteristics of the target population.318

All surveys are subject to sampling error, which is the expected probable difference between interviewing everyone in a population versus a scientific sampling drawn from that population. Sampling error should be adjusted to recognize the effect of weighting the data to better match the population. In this poll, the simple sampling error for 802 New Jersey adults is +/-2.69 percentage points at a 95 percent confidence interval. The design effect is 1.31, making the adjusted margin of error +/- 4.0 percentage points. Thus, if 50 percent of New Jersey adults in this sample favor a particular position, we would be 95 percent sure that the true figure is between 46 and 54 percent (50 +/- 4.0) if all New Jersey adults had been interviewed, rather than just a sample.

Sampling error does not take into account other sources of variation inherent in public opinion studies, such as non-response, question-wording, or context effects.

This telephone survey was fielded by Braun Research, Inc. with a sample from Dynata.

Weighted Telephone Sample Characteristics

802 New Jersey Adults

The sample was purchased from Marketing Systems Group and the research was funded by Fairleigh Dickinson University.

The Fairleigh Dickinson University Poll received an “A” rating from statistician Nate Silver’s FiveThirtyEight blog. The ratings measure both accuracy and bias for all major polling services in the United States, providing an update to similar research the poll watchers conducted in 2014. The Fairleigh Dickinson University Poll’s “A” rating puts it in the top 14 of the more than 380 polling institutes reviewed and graded from A+ through F. The Fairleigh Dickinson University Poll was found to have a 94 percent accuracy rate for predicting election results, and is one of only two A-rated polling institutes with zero bias to their rankings.

Tables and exact question wording and order

^[1] NCHS, National Health Interview Survey, 2012-2016; U.S. Census Bureau, American Community Survey, 2011-2015; and infoUSA.com consumer database, 2012-2016.

^[2] Blumberg SJ, Luke JV. Wireless substitution: Early release of estimates from the National Health Interview Survey, July–December 2015. National Center for Health Statistics. May 2016.

^[3] Blumberg SJ, Luke JV. Wireless substitution: Early release of estimates from the National Health Interview Survey, January-June 2018. National Center for Health Statistics. December 2018.