The categorical data depicts the success and failure rate of the low-fidelity wireframe above. There is not a large enough difference between the two to determine if the designs were successful.
There is an element of error involved in measuring anything. So, when we want to compare measurements, how do we decide whether any difference is due to the things being measured or due to error? In this video you will be introduced to the term “statistical significance” and why it’s important to know whether a difference is large enough to be meaningful or simply random chance.
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