Suppose Ally is an energy efficiency consultant z-statistic will not change Ally uses a significance level of a = 0.10 who is doing research for a hardware store that P-value will not change instead of a = 0.05. claims to promote energy efficiency. She wants decision will change to determine if the hardware store sells a conclusion will change higher proportion of LED light bulbs than the national average of 10.3%. She uses a z-statistic will not change computer program to select 60 calendar days P-value will increase Ally uses a two-tailed test instead of a from the previous year at random and obtains decision will not change one-tailed test and keeps the significance the stores sales records for those days. During level at a = 0.05. conclusion will not change those days, the hardware store sold 121 light bulbs, and 18 of them were LED. z-statistic will increase She performs a one-sample z-test for a P-value will decrease Ally increases her sample size to 139 light proportion, using a significance level of decision will change bulbs and the proportion of successes in her a = 0.05. She calculates a z-statistic of 1.656 conclusion will change sample remains the same. and a P-value of 0.049. Based on her test result, she decides to reject her null hypothesis Answer Bank and concludes that there is sufficient evidence z-statistic will decrease decision will not change to suggest that the amount of LED light bulbs that the hardware store sells is higher than the z-statistic will not change P-value will not change national average. Determine how changes to each of the conclusion will not change conclusion will change following test conditions influence the z-statistic, P-value, decision, and conclusion decision will change z-statistic will increase