That depends entirely on what you consider to be "expected range of values."
When you see a value like $3.43\pm 0.04$ (I will omit units for brevity), in many cases, it actually represents a normal probability distribution with a mean of $3.43$ and a standard deviation of $0.04$. If the $3.43\pm 0.04$ is the result of an experiment, for example, then the probability distribution applies to the true value of the thing the experiment was trying to measure. In particular, the experimenters are saying there is a 68% chance that the true value of the quantity is between $3.39$ and $3.47$, the so-called $1\sigma$ range. There is a 95% chance that the true value is between $3.35$ and $3.51$, the $2\sigma$ range. And so on.
Since the result with uncertainty really defines a probability distribution, when you want to compare another number to this result, the question you need to ask is not "is this number within the acceptable range?" (because there is no hard boundary to the range), but rather "what is the probability that the experiment would be at least this far off?" In the example in your question, the difference between the two values, $3.43$ and $3.48$, is $1.25\sigma$ (that's $1.25\times 0.04$). You can calculate that the probability of being off by $1.25\sigma$ or more is 21%; conversely, the probability of being within $1.25\sigma$ is 79%. So you could say there is a 79% probability that the two values are compatible. That's a fairly large probability, so it seems reasonable to say that these two values are, in fact, compatible (which is the more precise version of saying $3.48$ is within the "expected range").