Please show the process, I\'d like to understand how you worked the question. Th
ID: 3354595 • Letter: P
Question
Please show the process, I'd like to understand how you worked the question. Thank you
11. First, assume that no records in this sample are affected by the flaw you just explained in #10. You know that all fields EXCEPT for "g CO2e" were direct measurements from your data team. Someone else calculated the individual values in the "g CO2e" column. They copied and pasted their calculations as values, so you cannot verify their formula. You don't have time to track down their original calculations. The data team emailed you a number that was the average of the emission factors for this sample of shipments, which was 0.0000982297781627712. The calculations behind this average of factors accounted for type of transport and each shipment's share of payload capactity. Look at the other variables in the dataset. What could you do using this information to validate the data? Describe what you would do (genenally, step-by-step isn't necessary). (HINT: emissions is a function of distance, weight and emission factor.)
DATA SHEET
Question Answer 1. On the Data sheet, there should only be a maxiumum trans_cnt (transaction count) of 20 per order. Use conditional formating to visually identify if any orders exceed that amount. Show conditional formatting 2. How else could you have quickly answered #1? 3. Use formulas on the Data sheet to run basic descriptive stats on emissions (min, max, mean, median & mode, etc.). (HINT: use the Excel readings to look up formulas if you're unfamiliar) Show answers on Data below emissions column 4. Call out the top and bottom 10 percent of emissions Show conditional formatting 5. What is the range of highest 10% of emissions? 6. What is the range of lowest 10% of emissions? 7. How else would you group these emissions to better understand them? (A short written answer is fine. You don't have to show any work for this one.) 8. What is the longest distance any single item travelled? (You must use a formula to get credit!) 9. Using "copy of tot_d" and "copy of g CO2e" add an icon within that cell to demonstrate how big of a number that cell represents (HINT: use the Chandoo readings to find a better way than my tiny black and white pie charts.) Show conditional formatting 10. What is the major underlying flaw in this data set? (HINT: look at the variables provided and calculations made)11. First, assume that no records in this sample are affected by the flaw you just explained in #10. You know that all fields EXCEPT for "g CO2e" were direct measurements from your data team. Someone else calculated the individual values in the "g CO2e" column. They copied and pasted their calculations as values, so you cannot verify their formula. You don't have time to track down their original calculations. The data team emailed you a number that was the average of the emission factors for this sample of shipments, which was 0.0000982297781627712. The calculations behind this average of factors accounted for type of transport and each shipment's share of payload capactity. Look at the other variables in the dataset. What could you do using this information to validate the data? Describe what you would do (genenally, step-by-step isn't necessary). (HINT: emissions is a function of distance, weight and emission factor.)
Show answers on Data below the data setExplanation / Answer
Mean = 1847, Median = 268, Mode = 4, Min = 0, Max= 45987
4. The simplest way would be to sort the variable emission from lowest to highest. Then, the 10% of the total values 200 would be 20. Thus, we will have the top 20 and bottom 20 values as the top and bottom ten percent of emission.
Bottom 10%
Top 10%
0
3,610
0
3,633
1
3,741
1
3,985
3
4,299
3
4,598
3
4,664
3
4,851
4
5,331
4
5,593
4
6,199
4
7,373
4
7,845
4
10,157
4
11,618
5
14,462
5
29,264
5
30,826
5
40,758
5
45,987
5. The range of bottom 10% of emissions is (0 to 5)
6. The range of highest 10% of emission is (3610 to 45987).
8. 175265125 travels the highest distance of 5484. The formula used was "=MAX(A:A)”
Bottom 10%
Top 10%
0
3,610
0
3,633
1
3,741
1
3,985
3
4,299
3
4,598
3
4,664
3
4,851
4
5,331
4
5,593
4
6,199
4
7,373
4
7,845
4
10,157
4
11,618
5
14,462
5
29,264
5
30,826
5
40,758
5
45,987