Last year, I posted an infographic titled "Hypothesis Tests in One Picture". But formulating a hypothesis statement can be tricky--and you need one to even start choosing tests. That's why I like this simplified graphic.
Rather than starting with the type of data, it starts with a hypothesis statement. Do you think there's a relationship between the data? Or perhaps there's a difference in variances, distributions, or some other statistic. The starting point in analyzing data is often forming a hypothesis statement. And figuring that out is vital to getting the right answer from your data. With a hypotheses statement, you'll be in a good place to choose the right test or procedure to analyze your data.
A hypothesis statement is simply a short statement, a reworded question if you will; A question you want the answer to. For example, you might wonder if there's a difference in the different sections of your data (for example, higher averages), or you might wonder if there's a trend over time.
The picture below (based heavily on the aforementioned graphic) sums up some basic hypotheses, and leads to the tests and procedures that follow those statements.