Elections Standard Error
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it is possible in a very close election that a candidate might narrowly win the popular vote yet lose margin of error formula the election in the Electoral College. (See Wikipedia: Electoral College.) The observations margin of error calculator that follow pertain only to the ability of candidate preference polls to forecast the national popular vote margin of error definition in an election. The main point of these observations is that the results of such polls, especially in a close election, must be taken with a grain of
Margin Of Error In Polls
salt. The following table shows the results of polls conducted by three major polling organizations during the week just prior to the US presidential election of2000. Ineach case, the percentage of the national popular vote predicted by the poll for each candidate is displayed next to the percentage that was actually observed in the election. The final column acceptable margin of error shows the difference between the two, calculated as Predicted minus Observed. PollingOrganization Candidate PercentPredictedby Poll PercentObservedin Election Difference Zogby Gore 48% 48.4% -0.4% Bush 46% 47.9% -1.9% Other 6% 3.7% +2.3% Harris Gore 47% 48.4% -1.4% Bush 47% 47.9% -0.9% Other 6% 3.7% +2.3% Gallup Gore 45% 48.4% -3.4% Bush 47% 47.9% -0.9% Other 8% 3.7% +4.3% The Zogby poll correctly predicted that Mr.Gore would win the popular vote, though its projected 2% margin of victory was much greater than the 0.5% margin that actually occurred. At the other extreme, the Gallup poll predicted that Mr.Bush would win the popular vote by an equally comfortable 2% margin, which would have amounted to a margin of about two million votes, whereas he actually drew about half a million votes fewer than Mr.Gore. Inthe middle was the Harris poll, which correctly projected that candidates Gore and Bush would each receive about the same percentages of the popular vote, though in both cases it underestimated what these percentages would be. Notice that all
accurate, assuming you counted the votes correctly. (By the way, there's a whole other topic in math that describes the errors people can make when they try to measure things like that. But, for now, let's assume you can count with 100% accuracy.) Here's margin of error sample size the problem: Running elections costs a lot of money. It's simply not practical to conduct a public election
Margin Of Error Sample Size Calculator
every time you want to test a new product or ad campaign. So companies, campaigns and news organizations ask a randomly selected small number of people
Margin Of Error Excel
instead. The idea is that you're surveying a sample of people who will accurately represent the beliefs or opinions of the entire population. But how many people do you need to ask to get a representative sample? The best way to figure this one http://faculty.vassar.edu/lowry/polls/poll4.html is to think about it backwards. Let's say you picked a specific number of people in the United States at random. What then is the chance that the people you picked do not accurately represent the U.S. population as a whole? For example, what is the chance that the percentage of those people you picked who said their favorite color was blue does not match the percentage of people in the entire U.S. who like blue best? Of course, our little mental exercise here assumes you didn't http://www.robertniles.com/stats/margin.shtml do anything sneaky like phrase your question in a way to make people more or less likely to pick blue as their favorite color. Like, say, telling people "You know, the color blue has been linked to cancer. Now that I've told you that, what is your favorite color?" That's called a leading question, and it's a big no-no in surveying. Common sense will tell you (if you listen...) that the chance that your sample is off the mark will decrease as you add more people to your sample. In other words, the more people you ask, the more likely you are to get a representative sample. This is easy so far, right? Okay, enough with the common sense. It's time for some math. (insert smirk here) The formula that describes the relationship I just mentioned is basically this: The margin of error in a sample = 1 divided by the square root of the number of people in the sample How did someone come up with that formula, you ask? Like most formulas in statistics, this one can trace its roots back to pathetic gamblers who were so desperate to hit the jackpot that they'd even stoop to mathematics for an "edge." If you really want to know the gory details, the formula is derived from the standard deviation of the proportion of times that a researcher gets a sample "right," given a whole bunch of samples. Which is mathematical jargon for..."Trust me. It works, okay?" So a sample of just 1,600 people gives you a margin of error
Databank Current Data Providers Recent Acquisitions Deposit Data Membership Membership Fees List of Members Terms and Conditions Blog Support Support Overview Roper Center http://ropercenter.cornell.edu/support/polling-fundamentals-total-survey-error/ Tools iPOLL Support Data Support RoperExplorer Support Polling Concepts Polling Fundamentals Analyzing Polls Video Tutorials Classroom Materials Field of Public Opinion Field of Public Opinion Other Data Archives Professional Organizations Pioneers in Public Opinion Research Pursuing a Career in Survey Research About About the Center Data Curation Center History Bibliography Board of Directors Staff Cornell margin of Faculty Affiliates Job Opportunities Contact Us Giving Search iPOLL Search Datasets Polling Fundamentals - Total Survey Error Search Form Search Polling Fundamentals - Total Survey ErrorAdministrator2016-02-26T09:19:59+00:00 Polling Fundamentals Sections Introduction Sampling Total Survey Error Understanding Tables Glossary of Terminology This tutorial offers a glimpse into the fundamentals of public opinion polling. Designed for the novice, Polling margin of error Fundamentals provides definitions, examples, and explanations that serve as an introduction to the field of public opinion research. Total Survey Error What is meant by the margin of error? Most surveys report margin of error in a manner such as: "the results of this survey are accurate at the 95% confidence level plus or minus 3 percentage points." That is the error that can result from the process of selecting the sample. It suggests what the upper and lower bounds of the results are. Sampling error is the only error that can be quantified, but there are many other errors to which surveys are susceptible. Emphasis on the sampling error does little to address the wide range of other opportunities for something to go wrong. Total Survey Error includes Sampling Error and three other types of errors that you should be aware of when interpreting poll results: Coverage Error, Measurement Error, and Non-Response Error. What is sampling error? Sampling Error is the calculated statistical imprecision d