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This paper proposes a data-driven test for closed-loop stability. The test is based on a non-conservative stability condition that can be verified without having to actually implement the controller. It uses a set of measurements from the plant but does not rely on a plant model. For infinite data length, a validated controller is guaranteed to stabilize the plant. In practice, however, only a finite number of noisy data can be used, and thus only an estimate of the stability condition can be obtained. A reliable stability test needs to take this estimation uncertainty into account, which introduces conservatism. In the proposed test, two variables are available to control the trade-off between reliability and conservatism in an intuitive way. A simulation example shows the effectiveness of the stability test.