Answer:
B. Fail to reject null hypothesis .
Step-by-step explanation:
We are given that a systems analyst tests a new algorithm designed to work faster than the currently-used algorithm.
Also, = true mean completion time for the new algorithm
= true mean completion time for the current algorithm
<em>Null Hypothesis, </em><em> : </em><em> {Both new and current algorithm has same </em>
<em> completion time}</em>
<em>Alternate Hypothesis, </em><em> : </em><em> {New algorithm has lower mean </em>
<em> completion time than current algorithm}</em>
The test statistics we use here will be :
follows
where, = 18.78 hours and = 19.06 hours
= 5.614 hours and = 5.012 hours
= 46 and = 46
= 5.321
Here, we use t test statistics because we know nothing about population standard deviations.
Test statistics = follows
= -0.2524
<em>At 0.1 or 10% level of significance t table gives a critical value between -1.296 and -1.289 at 90 degree of freedom. Since our test statistics is more than the critical table value of t as -0.2524 > -1.296 to -1.289 so we have insufficient evidence to reject null hypothesis.</em>
Therefore, we conclude that new algorithm has same mean completion time with that of current algorithm.