Produtos

A SurveyMonkey foi feita para atender a todos os casos de uso e necessidades. Explore nosso produto para saber como a SurveyMonkey pode te ajudar.

Obtenha insights baseados em dados com questionários online.

Integre seus dados com mais de 100 aplicativos e plug-ins para produzir mais.

Crie e personalize formulários para coletar dados e pagamentos.

Crie pesquisas e descubra insights rapidamente com nossa IA integrada.

Soluções feitas especialmente para todas as suas necessidades de pesquisa de mercado.

Modelos

Meça a satisfação e a fidelidade de clientes à sua empresa.

Saiba o que seus clientes mais querem e torne-os defensores da sua marca.

Obtenha insights práticos para melhorar a experiência de usuários.

Colete informações de contato de clientes potenciais, convidados e outros.

Facilmente colete e monitore confirmações de presença para seu próximo evento.

Descubra o que participantes querem para melhorar seu próximo evento.

Descubra insights para melhorar o envolvimento de colaboradores e promover resultados cada vez melhores.

Obtenha feedback de participantes para fazer reuniões cada vez melhores.

Use o feedback de seus colegas para melhorar o desempenho de colaboradores.

Crie cursos e métodos de ensino cada vez melhores.

Saiba como estudantes podem avaliar o conteúdo e a apresentação do curso.

Descubra o que seus clientes acham das suas ideias de novos produtos.

Recursos

Práticas recomendadas para o uso de pesquisas e dados de pesquisas.

Nosso blog sobre pesquisas, dicas para negócios e muito mais.

Tutoriais e guias de como usar a SurveyMonkey.

Como grandes marcas geram crescimento com a SurveyMonkey.

Falar conoscoFazer login
Falar conoscoFazer login

Probability sampling

Choosing the right sample for statistically-significant results

How do you conduct an accurate national survey when there are 330 million people living in the U.S.?

It would be impossible to send a survey to every single person, but you can use probability sampling to get data that’s just as good even if it comes from a much smaller population.

Probability sampling uses statistical theory to randomly select a small group (a sample) from a larger population, and then predicts the likelihood that all their responses put together will match those of the overall population.

Probability sampling has two equally important requirements:

  • Everyone in your population must have a non-zero chance of being selected (i.e. a chance you’ll send them a survey).
  • You must know, specifically, what that chance of being selected is for each person.

Following these two rules will help you choose an appropriate sample that represents the overall population. With the right sample, your results will be equally as valid as if they had come from a survey of the whole population.

You never want to knowingly exclude someone in your population from being selected into your sample. Watch out for times when particular groups might be unintentionally prevented from participating.

For example, let’s say you want to understand public opinion on an expansive new immigration law. Will you offer a Spanish language version of your survey? You should. If you don’t, you’ll likely miss a lot of first-generation Hispanic immigrants who aren’t comfortable answering questions in English but who have clear and consistent views on immigration. Your survey results won’t match up with true public opinion.

If you can’t give everyone in your population a chance at completing your survey, your sample with be non-representative and, therefore, biased.

In simple random sampling, all members of the population have an equal chance of being selected, and the selection is done randomly. As the name indicates, this is the simplest sampling strategy, but it is also the most prone to bias. The smaller your sample size is compared to your overall population, the less likely you are to draw a reliable sample totally at random. Try using our sample size calculator to get improved results.

Many populations can be divided into smaller groups that don’t overlap but represent the entire population when put together. When sampling, we can take these groups (or strata) and draw a sample from each separately. It’s common to stratify by sex, age, or ethnicity, assigning different selection probabilities to different strata. As long as all sample members are included in one stratum and all the strata are sampled, the probability design still holds.

Cluster sampling is most often used to save costs when surveying populations that are very spread out geographically. Instead of selecting people at random, different geographic areas (or clusters) are selected at random, and then some or all of the members of the selected clusters are surveyed.

Think through all the people that you’re interested in hearing from, but also be aware of anyone who should be deliberately excluded.

Ideally, your frame should include all members of your population of interest (and no one who is not in your population of interest).

Do you want clusters and strata? Do you want all sample members to have equal probabilities of selection?

Depending on the population you’re trying to survey, you might have a hard time finding an appropriate sample frame. Even if you have a good frame, deciding on the best selection strategy will force you to make trade-offs between cost, representation, quality, and timeliness.

Getting people to respond to a true probability survey is difficult, because they are unlikely to be interested in the survey topic or to be compensated for the time and effort it takes to complete the survey.

Many of these problems can be solved with non-probability sampling, which (despite its name) still draws from probability and sampling theory to select an appropriate survey sample.

If you have unlimited resources or a small population of interest, probability sampling may not be necessary. But, in most cases, drawing a probability sample will save you time, money, and a lot of frustration. You usually can’t survey everyone, but you can always give everyone the chance to be surveyed; this is what probability sampling accomplishes.

Diretório de kits de ferramentas

Descubra nossos kits de ferramentas desenvolvidos para te ajudar a aproveitar feedbacks no seu cargo ou seu setor.

Práticas recomendadas para questionários

Conheça nossas práticas recomendadas e tire o maior proveito possível da sua próxima pesquisa. Explore nossos guias de pesquisa e comece hoje mesmo.

Crie e personalize formulários de inscrição e candidatura online facilmente

Crie e personalize formulários de inscrição e candidatura facilmente. Crie seu design e publique mais rápido usando nossos modelos gratuitos.

Principais tendências de pesquisa em 2024

Nova pesquisa sobre trending topics de 2024 e práticas recomendadas de pesquisa. Obtenha insights dos dados coletados na plataforma da SurveyMonkey.