Data analysis is only as good as the quality of the raw data you put in. To get meaningful results, you need to make sure you are analysing the right information. The following questions should help you make sure you are on the right track.

Do you have the right sample?

If you’re looking for information about a specific group or product, make sure your sample is relevant. For example, if your market is retirees, a poll of university students probably won’t yield much relevant information. If you are looking at broader trends, you probably want a true random sample.

Is your sample really random?

This is a common stumbling block for everyone from students to professional pollsters. Many factors can bias a sample—perhaps you’re only collecting data in one postcode (people in any given neighbourhood tend to have similar lifestyles), or are soliciting responses from a magazine whose readers have strong political views in a certain direction.

Is your sample big enough?

Thirty data points is the bare minimum you can use for a significant result. A larger set will return more reliable information. However, the benefits of increasing your data set size decrease after you’ve collected several thousand data points, so you don’t need to go overboard.