Importance of Water - California

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They survey was conducted over two days from September 13 - 15, 2017. It was conducted through Google Surveys. It had a targeted number of responses of 1,000 and was distributed statewide to California. 


Additional Survey Findings: 

  • When asked what is the most important sector to spend their tax dollars on; a small 9.5% of respondents answered Water. In fact, the only other sectors they would avoid more are Power Supply and Infrastructure (8.7%) and Welfare (3.9%)


  • An overwhelming 38.7% of respondents believe that education is the most undervalued industry in comparison to Waste Management (14.9%), Emergency Workers (14.3%), Water and Wastewater Management (13.7%), Public Transit (13.0%) and Electricity (5.4%)


  • 38.9% of 18-24 year old female respondents spend longer than 15 minutes in the shower. Whereas only 6.1% of female respondents over the age of 65 answered the same. 


  • Young men (18-24 Years old)  spend as little time as possible in the shower with 32.8% stating they spend between 1-5 minutes in the shower. Additionally another 32.8% stated they spend between 5-10 minutes in the shower. 


  • No one can decide who cares the most about water. When asked which region cared the most about their water, the results were split: 40.1% South California, 31.8% North California, 18.4% West California, 9.7% East California. 


  • Men care more about money when prepping for a natural disaster. 7.5% of men would reach for their wallets first when prepping in comparison to 4.4% of women. 


  • In comparison to other surveys conducted by FluksAqua, California (9.5%) cares more about their tax dollars being spent on water than Montana (8.9%) and Texas (8.0%). However, New Mexico cares the most at 9.9%


Raw Data

RAW DATA - Question 1

RAW DATA - Question 2

RAW DATA - Question 3

RAW DATA - Question 4

RAW DATA - Question 5


Methodology (From Google Surveys)

Google Surveys makes use of the inferred demographic and location information to employ stratified sampling by distributing the surveys based on the targeted audience to our publisher network and/or android smartphone users. We infer demographics through respondents' browsing history (e.g., infer geography from IP address), then we match them against existing government statistical data. Google Surveys uses post-stratification weighting to compensate for sample deficiencies to remove bias among the survey sample. This gives a more accurate result with lower root mean square error (RMSE) which also makes the results better represent the Current Population Survey (CPS).

Google Surveys performs equal to or better than existing probability and non-probability based Internet survey panels. A full description of the Google Surveys methodology can be found in this whitepaper or the product overview.

Rachel Ott