Suppose ally is an energy efficiency consultant who is doing research for a hardware store that claims to promote energy efficiency. she wants to determine if the hardware store sells a higher proportion of led light bulbs than the national average of 10.3%. she uses a computer program to select 60 calendar days ally uses a significance level of α = 0.10 instead of α 0.05. z-statistic will not change p-value will not change decision will change conclusion will change om the previous year at random and obtains the stores sales records for those davs. during those days, the hardware store sold 121 light bulbs, and 18 of them were led z-statistic will not change p-value will increase decision will not change conclusion will not change ally uses a two-tailed test instead of a one-tailed test and keeps the significance level at α 0.05 she performs a one-sample z-test for a proportion, using a significance level of α-0.05. she calculates a z-statistic of 1.656 and a p-value of 0.049. based on her test result, she decides to reject her null hypothesis and concludes that there is sufficient evidence to suggest that the amount of led light bulbs that the hardware store sells is higher than the national average z-statistic will not change p-value will not change decision will not change conclusion will not change ally increases her sample size to 139 light bulbs and the proportion of successes in her sample remains the same answer bank