Question: Several colleagues, including the CEO, are discussing the results of a hypothesis test conducted in China to help determine whether the company should sell more widgets there, which could be very lucrative. The null hypothesis was rejected (Ho: the company would lose money or make no profit) in favor of the alternate hypothesis (H1: the company would make a profit). The p-value turned out to be .12, and the CEO is breaking a sweat, thinking that’s a high p-value. You listen in and decide to explain to them how to interpret the p-value. What do you say? Why does it not really matter that much what the significance level was? These execs are not statistically inclined, Explain in lay terms so they can truly understand.