Question

Why is it more accurate to draw conclusions from a large sample than from a small sample

Answer 1

Answer:

The Importance and Effect of Sample Size

When conducting research about your customers, patients or products it’s usually impossible, or at least impractical, to collect data from all of the people or items that you are interested in. Instead, we take a sample (or subset) of the population of interest and learn what we can from that sample about the population.

There are lots of things that can affect how well our sample reflects the population and therefore how valid and reliable our conclusions will be. In this blog, we introduce some of the key concepts that should be considered when conducting a survey, including confidence levels and margins of error, power and effect sizes. (See the glossary below for some handy definitions of these terms.) Crucially, we’ll see that all of these are affected by how large a sample you take, i.e., the sample size.

Confidence and Margin of Error

Let’s start by considering an example where we simply want to estimate a characteristic of our population, and see the effect that our sample size has on how precise our estimate is.

The size of our sample dictates the amount of information we have and therefore, in part, determines our precision or level of confidence that we have in our sample estimates. An estimate always has an associated level of uncertainty, which depends upon the underlying variability of the data as well as the sample size. The more variable the population, the greater the uncertainty in our estimate. Similarly, the larger the sample size the more information we have and so our uncertainty reduces.

Suppose that we want to estimate the proportion of adults who own a smartphone in the UK. We could take a sample of 100 people and ask them. Note: it’s important to consider how the sample is selected to make sure that it is unbiased and representative of the population – we’ll blog on this topic another time.

The larger the sample size the more information we have and so our uncertainty reduces.