1. Define the null and alternative hypothesis for this test in mathematical terms and in words.
2. Report the level of significance.
3. Include the test statistic and the P-value. See Step 3 in the Python script. (Note that Python methods return two-tailed P-values. You must report the correct P-value based on the alternative hypothesis.)
4. Provide your conclusion and interpretation of the results. Should the null hypothesis be rejected? Why or why not?

Diameters data frame diameters 2. 72 2. 60 1. 82 2. 73 1.93 2. 13 2.37 3. 08 1.95 3. 05 2. 74 2.23 2.36 13 2. 21 14 3.34 15 2. 50 16 2.56 17 1. 63 18 2. 26 19 2. 43 20 2. 07 21 2.20 22 2.34 23 2. 03 24 2. 28 25 2. 04 26 2. 09 27 1. 77 28 3.37 29 2. 16 30 3. 05 31 1.50 32 2. 77 33 3. 10 34 2.94 35 2. 10 36 2.60 37 2. 52 38 2. 58 39 2. 76 40 3. 15 41 2.59 42 2. 52 43 2. 91 44 1. 32 45 2. 69 46 2.59 47 3. 05 48 3. 26 49 2. 2490% confidence interval (unrounded) = (2. 3482912846323325, 2.5809087153676673) 90% confidence interval (rounded) = ( 2.35 , 2.58 ) 99% confidence interval (unrounded) = (2. 2824613632281547, 2. 646738636771845) 99% confidence interval (rounded) = ( 2.28 , 2.65 )z-test hypothesis test for population mean test-statistic = 2.43 two tailed p-value = 0.0149