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Surveys can be great tools for internal decision-making. Leverage Material’s expert insights to optimize your results.
Marketers know that it’s better to advertise a product for $89.99 instead of $90 because a difference of just one penny can make a subtle psychological impact.
Psychology also comes into play in the research world, where a sample size of 1,000 sounds much more reliable to research leaders than a sample of 900. This qualitative form of confidence, which tends to drive the use of particularly large samples, is especially pertinent if the results will be published in the media.
But most primary research is proprietary and its results held close to the vest, How do you decide how much to invest in survey sample sizes that will be used only for internal decision-making? This requires some understanding of the dreaded field of statistics.
Empowerment through understanding
Even experienced researchers can struggle to understand basic statistical principles and these key elements prove downright daunting to most end users of their results.
A secure understanding of basic survey sampling topics, such as sample sizes, sampling errors, confidence levels, confidence intervals, and statistically significant differences can ensure that researchers can carry out impactful surveys and empower brands with the knowledge to make crucial business decisions.
Get confident about surveying
When conducting a survey, you can never be 100% confident about the figures you collect; but with a solid understanding of sample sizes and basic statistics, both researchers and their stakeholders can be confident that the results are actionable.
Whether you are just starting out or looking for a refresher, Material’s expert team has put together a guide to statistical principles for researchers and how they can be leveraged to benefit your brand.
What you’ll learn
- Key terms and their definitions,
- Confidence intervals vs. confidence levels and the limitations of each,
- How to determine the strength of confidence levels for decision-driving work
- The risk and reward of larger sample sizes,
- How to make the most of smaller sample sizes,
- Tips and best practices for success, and more!