Excel Function Exercises 401
Ex1
| Tech Companies | |||||
| Microsoft | |||||
| Apple | |||||
| Microsoft | |||||
| Apple | |||||
| Microsoft | |||||
| Microsoft | |||||
| Sony | |||||
| Apple | |||||
| Microsoft | |||||
| Oracle | |||||
| IBM | |||||
| Lenovo | |||||
| IBM | |||||
| Oracle | |||||
| Lenovo | |||||
| Sony | |||||
| Lenovo | |||||
| Linked-In | |||||
| Microsoft | |||||
| IBM | |||||
| Oracle | |||||
| Microsoft | |||||
| Lenovo | |||||
| IBM | |||||
| IBM | |||||
| Apple | |||||
| Lenovo | |||||
| Microsoft | |||||
| Oracle | |||||
| Oracle | |||||
| Linked-In | |||||
| IBM | |||||
| Linked-In | |||||
| Apple | |||||
| Sony | |||||
| Oracle | |||||
| IBM | |||||
| Lenovo | |||||
| Sony | |||||
| Microsoft | |||||
| Apple | |||||
| Linked-In | |||||
| Microsoft | |||||
| Microsoft | |||||
| Sony | |||||
| Sony | |||||
| Oracle | |||||
| Linked-In | |||||
| IBM | |||||
| IBM | |||||
| Microsoft | |||||
| Lenovo | |||||
| Apple | |||||
| Sony | |||||
| Apple | |||||
| Apple | |||||
| Apple | |||||
| Microsoft | |||||
| Lenovo | |||||
| Oracle | |||||
| Apple | |||||
| Microsoft | |||||
| Apple | |||||
| IBM | |||||
| IBM | |||||
| Lenovo | |||||
| Oracle | |||||
| Apple | |||||
| Oracle | |||||
| Microsoft | |||||
| Sony | |||||
| Apple | |||||
| Oracle | |||||
| Linked-In | |||||
| Apple | |||||
| Oracle | |||||
| Lenovo | |||||
| Apple | |||||
| Sony | |||||
| Microsoft | |||||
| Lenovo | |||||
| Microsoft | |||||
| Linked-In | |||||
| Sony | |||||
| Lenovo | |||||
| Sony | |||||
| Sony | |||||
| IBM | |||||
| Microsoft | |||||
| Lenovo | |||||
| Apple | |||||
| Lenovo | |||||
| Apple | |||||
| Lenovo | |||||
| Lenovo | |||||
| IBM | |||||
| Oracle | |||||
| Oracle | |||||
| IBM | |||||
| Apple | |||||
| Sony | |||||
| Apple | |||||
| Apple | |||||
| Sony | |||||
| Apple | |||||
| Sony | |||||
| Linked-In | |||||
| Lenovo | |||||
| Microsoft | |||||
| Sony | |||||
| IBM | |||||
| Lenovo | |||||
| Linked-In | |||||
| IBM | |||||
| Microsoft | |||||
| Lenovo | |||||
| Sony | |||||
| Sony | |||||
| Linked-In | |||||
| Linked-In | |||||
| Oracle | |||||
| Apple | |||||
| Oracle | |||||
| Microsoft | |||||
| Apple | |||||
| Lenovo | |||||
| Apple | |||||
| Lenovo | |||||
| Apple | |||||
| Microsoft | |||||
| Apple | |||||
| Oracle | |||||
| Oracle | |||||
| Microsoft | |||||
| IBM | |||||
| Lenovo | |||||
| Sony | |||||
| Sony | |||||
| Sony | |||||
| Lenovo | |||||
| Apple | |||||
| Microsoft | |||||
| Sony | |||||
| Apple | |||||
| Sony | |||||
| Apple | |||||
| Apple | |||||
| IBM | |||||
| IBM | |||||
| Microsoft | |||||
| IBM | |||||
| Oracle | |||||
| Linked-In | |||||
| Sony | |||||
| Sony | |||||
| IBM | |||||
| Microsoft | |||||
| Sony | |||||
| Oracle | |||||
| Lenovo | |||||
| IBM | |||||
| Apple | |||||
| Lenovo | |||||
| Apple | |||||
| Lenovo | |||||
| Sony | |||||
| Lenovo | |||||
| IBM | |||||
| Sony | |||||
| IBM | |||||
| Sony | |||||
| Lenovo | |||||
| Oracle | |||||
| Apple | |||||
| Linked-In | |||||
| IBM | |||||
| Microsoft | |||||
| Apple | |||||
| IBM | |||||
| Linked-In | |||||
| Lenovo | |||||
| Apple | |||||
| Apple | |||||
| Sony | |||||
| Microsoft | |||||
| IBM | |||||
| Oracle | |||||
| Sony | |||||
| Oracle | |||||
| Oracle | |||||
| Sony | |||||
| Oracle | |||||
| Oracle | |||||
| Lenovo | |||||
| Apple | |||||
| Lenovo | |||||
| Sony | |||||
| Sony | |||||
| Lenovo | |||||
| Oracle | |||||
| Microsoft | |||||
| Apple | |||||
| IBM | |||||
| Microsoft | |||||
| Apple | |||||
| Lenovo | |||||
| Lenovo | |||||
| Lenovo | |||||
| Linked-In | |||||
| Microsoft | |||||
| IBM | |||||
| Oracle | |||||
| IBM | |||||
| Linked-In | |||||
| Apple | |||||
| Linked-In | |||||
| Lenovo | |||||
| Linked-In | |||||
| Lenovo | |||||
| Oracle | |||||
| Oracle | |||||
| Linked-In | |||||
| Oracle | |||||
| Microsoft | |||||
| Linked-In | |||||
| Apple | |||||
| Oracle |
Exercise 1: 1. Using the Countif function, make a table that lists the total count for each Technology Company that appears in the list in Column F. 2. Using the sort function, put the list created in decreasing order based upon the number of times each Technology Company appears on the list. 3. Make a chart of the Total Count of Each Technology Company. Hint: A Bar chart may work best for this chart. 4. Use the textbox to describe in a couple of paragraphs the meaning of the results obtained for Exercise 1. *Keep the table and chart created for Exercise 1 in this tab. Total Points: 25
Describe the meaning of results obtained for Exercise 1 in 3 paragraphs (5 points)
Ex2
| Region | Revenue | Expenses | |||||
| Asia | $ 8,249.33 | $ 594.88 | |||||
| Asia | $ 6,557.87 | $ 83.34 | |||||
| Africa | $ 6,180.04 | $ 551.27 | |||||
| Asia | $ 9,915.45 | $ 336.86 | |||||
| Africa | $ 4,047.67 | $ 481.01 | |||||
| Africa | $ 4,797.09 | $ 962.36 | |||||
| Africa | $ 6,537.80 | $ 931.97 | |||||
| Asia | $ 3,151.42 | $ 848.21 | |||||
| US and Europe | $ 9,504.78 | $ 827.56 | |||||
| Asia | $ 9,378.14 | $ 566.80 | |||||
| US and Europe | $ 6,772.13 | $ 436.88 | |||||
| Africa | $ 1,854.63 | $ 930.55 | |||||
| US and Europe | $ 8,303.94 | $ 680.75 | |||||
| Africa | $ 6,741.46 | $ 418.03 | |||||
| Africa | $ 4,151.44 | $ 336.41 | |||||
| Africa | $ 7,972.30 | $ 917.14 | |||||
| US and Europe | $ 10,331.58 | $ 440.47 | |||||
| Africa | $ 3,695.19 | $ 217.66 | |||||
| Africa | $ 7,904.29 | $ 764.58 | |||||
| Asia | $ 849.26 | $ 94.52 | |||||
| US and Europe | $ 7,157.63 | $ 915.92 | |||||
| Asia | $ 3,712.57 | $ 432.55 | |||||
| Africa | $ 7,596.44 | $ 134.82 | |||||
| Africa | $ 2,198.66 | $ 1,037.29 | |||||
| US and Europe | $ 4,724.00 | $ 463.29 | |||||
| Asia | $ 1,331.26 | $ 959.23 | |||||
| Asia | $ 2,743.80 | $ 222.92 | |||||
| US and Europe | $ 5,038.31 | $ 306.96 | |||||
| Africa | $ 10,458.27 | $ 692.76 | |||||
| Africa | $ 7,567.04 | $ 720.32 | |||||
| US and Europe | $ 7,688.43 | $ 851.85 | |||||
| Africa | $ 4,023.23 | $ 166.49 | |||||
| Asia | $ 4,551.60 | $ 701.05 | |||||
| Asia | $ 2,665.11 | $ 654.98 | |||||
| Africa | $ 6,589.12 | $ 278.19 | |||||
| Asia | $ 5,220.43 | $ 589.17 | |||||
| Asia | $ 7,282.19 | $ 387.55 | |||||
| Africa | $ 6,444.58 | $ 258.50 | |||||
| Africa | $ 10,299.03 | $ 287.80 | |||||
| Africa | $ 9,841.23 | $ 824.48 | |||||
| Africa | $ 8,237.85 | $ 48.30 | |||||
| Asia | $ 6,221.25 | $ 414.88 | |||||
| Asia | $ 5,401.24 | $ 877.97 | |||||
| Africa | $ 10,013.81 | $ 807.85 | |||||
| US and Europe | $ 8,466.70 | $ 450.57 | |||||
| Africa | $ 8,382.21 | $ 958.25 | |||||
| Africa | $ 8,105.42 | $ 647.65 | |||||
| Africa | $ 10,051.26 | $ 1,003.73 | |||||
| Africa | $ 3,667.20 | $ 680.71 | |||||
| Africa | $ 7,822.06 | $ 924.36 | |||||
| Africa | $ 4,575.53 | $ 657.65 | |||||
| Africa | $ 3,178.20 | $ 756.21 | |||||
| Africa | $ 1,734.41 | $ 864.15 | |||||
| Asia | $ 8,601.07 | $ 666.92 | |||||
| Asia | $ 8,328.45 | $ 898.71 | |||||
| Asia | $ 9,715.27 | $ 536.26 | |||||
| Asia | $ 4,722.77 | $ 837.71 | |||||
| Asia | $ 3,434.69 | $ 574.12 | |||||
| Africa | $ 8,696.76 | $ 581.44 | |||||
| Asia | $ 9,195.08 | $ 1,000.67 | |||||
| US and Europe | $ 4,168.87 | $ 650.90 | |||||
| US and Europe | $ 885.24 | $ 323.98 | |||||
| Asia | $ 3,222.21 | $ 760.28 | |||||
| Africa | $ 3,185.18 | $ 455.46 | |||||
| Africa | $ 5,050.98 | $ 618.33 | |||||
| Africa | $ 306.08 | $ 275.31 | |||||
| Africa | $ 9,598.98 | $ 613.29 | |||||
| Africa | $ 10,338.80 | $ 979.85 | |||||
| Asia | $ 7,350.61 | $ 271.99 | |||||
| Africa | $ 7,506.47 | $ 408.01 | |||||
| Africa | $ 1,939.78 | $ 413.94 | |||||
| US and Europe | $ 7,692.22 | $ 1,015.87 | |||||
| US and Europe | $ 1,060.49 | $ 607.34 | |||||
| Asia | $ 738.51 | $ 431.47 | |||||
| Africa | $ 8,174.84 | $ 206.65 | |||||
| Africa | $ 4,368.81 | $ 203.38 | |||||
| Africa | $ 1,292.52 | $ 123.11 | |||||
| US and Europe | $ 2,210.75 | $ 465.53 | |||||
| US and Europe | $ 4,240.74 | $ 737.07 | |||||
| Africa | $ 5,927.04 | $ 501.24 | |||||
| Africa | $ 2,597.35 | $ 489.99 | |||||
| Africa | $ 9,549.49 | $ 835.02 | |||||
| Africa | $ 3,931.33 | $ 191.42 | |||||
| Africa | $ 8,578.80 | $ 670.24 | |||||
| US and Europe | $ 1,946.14 | $ 273.51 | |||||
| Asia | $ 9,021.02 | $ 402.06 | |||||
| Asia | $ 5,575.67 | $ 148.33 | |||||
| US and Europe | $ 1,193.07 | $ 148.13 | |||||
| Africa | $ 10,340.53 | $ 250.08 | |||||
| Africa | $ 5,512.77 | $ 542.62 | |||||
| Asia | $ 2,556.00 | $ 824.13 | |||||
| Africa | $ 10,157.81 | $ 508.17 | |||||
| Asia | $ 8,921.52 | $ 259.33 | |||||
| US and Europe | $ 10,494.44 | $ 565.43 | |||||
| Asia | $ 7,007.77 | $ 765.69 | |||||
| Asia | $ 4,811.04 | $ 193.17 | |||||
| Africa | $ 8,657.83 | $ 171.60 | |||||
| Asia | $ 8,204.32 | $ 278.75 | |||||
| Africa | $ 4,246.88 | $ 644.52 |
Exercise 2: There are 3 Regions for which data are collected. See colums F - H. These are: US and Europe, Asia and Africa. 1. Using the SORT function Make a table listing Total Revenue and Expenses for each region. 2. Make a chart of Total Revenue and Expenses for each region. 3. Use the textbox to describe in a couple of paragraphs the meaning of the results obtained for Exercise 2. *Keep the table and chart for Exercise 2 in this tab. Total Points: 35
Describe the meaning of the results obtained for Exercise 2 in at least 3 paragraps (10 points).
Ex7
| Group Name | Group Segment | Revenue | Expenses | Net Income/Loss | Data | ||||||||
| Postcards Store | Big | 8249.3276698127 | 594.878242008 | 7654.4494278048 | Group Segment | Sum of Expenses | Sum of Revenue | ||||||
| Randles Roadshack | Small | 6557.8729832219 | 83.3393859721 | 6474.5335972499 | Big | 41586390.9696846 | 48945091.5423439 | ||||||
| Examineers Inc | Medium | 6180.0357471981 | 551.2667803915 | 5628.7689668066 | Medium | 2310.7997296187 | 22222.6176752647 | ||||||
| Buttersworth Co | Small | 9915.4543112251 | 336.8576784372 | 9578.5966327879 | Small | 2186.2988659312 | 30444.5522903428 | ||||||
| FASST Trax | Small | 4047.6691780881 | 481.0083008923 | 3566.6608771959 | Grand Total | 41590888.0682801 | 48997758.7123095 | ||||||
| Hula Hoopers | Big | 4797.0875045761 | 962.3550943443 | 3834.7324102318 | |||||||||
| Hehehe | Medium | 6537.8001010167 | 931.9697247837 | 5605.830376233 | |||||||||
| Marleyville Tea | Small | 3151.4227753704 | 848.2135170178 | 2303.2092583526 | |||||||||
| Creepy Lada | Medium | 9504.7818270498 | 827.5632244434 | 8677.2186026064 | |||||||||
| Jokes R Us | Big | 9378.1404699585 | 566.7976536033 | 8811.3428163552 | |||||||||
| Petie's Palace | Small | 6772.1330424373 | 436.8799836118 | 6335.2530588255 | |||||||||
| Ramone's Castle | Big | 48922666.9867 | 41584266.9386946 | 7338400.04800493 |
Exercise 7 Because Ramone's Castle is a high outlier, take it out of the pivot table that is already done. Show Revenue and Expenses by Group Segment (excluding Ramone's Castle). Have "Sum of Revenue" be the left column (you may need to switch the two columns). Keep pivot table in this tab.
Ex3
| Region | Revenue | Expenses | Total Revenue and Expenses | |||||||
| Asia | $ 8,249.33 | $ 594.88 | Region | Revenue | Expenses | |||||
| Asia | $ 6,557.87 | $ 83.34 | US and Europe | |||||||
| Africa | $ 6,180.04 | $ 551.27 | Asia | |||||||
| Asia | $ 9,915.45 | $ 336.86 | Africa | |||||||
| Africa | $ 4,047.67 | $ 481.01 | ||||||||
| Africa | $ 4,797.09 | $ 962.36 | ||||||||
| Africa | $ 6,537.80 | $ 931.97 | Average Revenue and Expenses | |||||||
| Asia | $ 3,151.42 | $ 848.21 | Region | Revenue | Expenses | |||||
| US and Europe | $ 9,504.78 | $ 827.56 | US and Europe | |||||||
| Asia | $ 9,378.14 | $ 566.80 | Asia | |||||||
| US and Europe | $ 6,772.13 | $ 436.88 | Africa | |||||||
| Africa | $ 1,854.63 | $ 930.55 | ||||||||
| US and Europe | $ 8,303.94 | $ 680.75 | ||||||||
| Africa | $ 6,741.46 | $ 418.03 | ||||||||
| Africa | $ 4,151.44 | $ 336.41 | ||||||||
| Africa | $ 7,972.30 | $ 917.14 | ||||||||
| US and Europe | $ 10,331.58 | $ 440.47 | ||||||||
| Africa | $ 3,695.19 | $ 217.66 | ||||||||
| Africa | $ 7,904.29 | $ 764.58 | ||||||||
| Asia | $ 849.26 | $ 94.52 | ||||||||
| US and Europe | $ 7,157.63 | $ 915.92 | ||||||||
| Asia | $ 3,712.57 | $ 432.55 | ||||||||
| Africa | $ 7,596.44 | $ 134.82 | ||||||||
| Africa | $ 2,198.66 | $ 1,037.29 | ||||||||
| US and Europe | $ 4,724.00 | $ 463.29 | ||||||||
| Asia | $ 1,331.26 | $ 959.23 | ||||||||
| Asia | $ 2,743.80 | $ 222.92 | ||||||||
| US and Europe | $ 5,038.31 | $ 306.96 | ||||||||
| Africa | $ 10,458.27 | $ 692.76 | ||||||||
| Africa | $ 7,567.04 | $ 720.32 | ||||||||
| US and Europe | $ 7,688.43 | $ 851.85 | ||||||||
| Africa | $ 4,023.23 | $ 166.49 | ||||||||
| Asia | $ 4,551.60 | $ 701.05 | ||||||||
| Asia | $ 2,665.11 | $ 654.98 | ||||||||
| Africa | $ 6,589.12 | $ 278.19 | ||||||||
| Asia | $ 5,220.43 | $ 589.17 | ||||||||
| Asia | $ 7,282.19 | $ 387.55 | ||||||||
| Africa | $ 6,444.58 | $ 258.50 | ||||||||
| Africa | $ 10,299.03 | $ 287.80 | ||||||||
| Africa | $ 9,841.23 | $ 824.48 | ||||||||
| Africa | $ 8,237.85 | $ 48.30 | ||||||||
| Asia | $ 6,221.25 | $ 414.88 | ||||||||
| Asia | $ 5,401.24 | $ 877.97 | ||||||||
| Africa | $ 10,013.81 | $ 807.85 | ||||||||
| US and Europe | $ 8,466.70 | $ 450.57 | ||||||||
| Africa | $ 8,382.21 | $ 958.25 | ||||||||
| Africa | $ 8,105.42 | $ 647.65 | ||||||||
| Africa | $ 10,051.26 | $ 1,003.73 | ||||||||
| Africa | $ 3,667.20 | $ 680.71 | ||||||||
| Africa | $ 7,822.06 | $ 924.36 | ||||||||
| Africa | $ 4,575.53 | $ 657.65 | ||||||||
| Africa | $ 3,178.20 | $ 756.21 | ||||||||
| Africa | $ 1,734.41 | $ 864.15 | ||||||||
| Asia | $ 8,601.07 | $ 666.92 | ||||||||
| Asia | $ 8,328.45 | $ 898.71 | ||||||||
| Asia | $ 9,715.27 | $ 536.26 | ||||||||
| Asia | $ 4,722.77 | $ 837.71 | ||||||||
| Asia | $ 3,434.69 | $ 574.12 | ||||||||
| Africa | $ 8,696.76 | $ 581.44 | ||||||||
| Asia | $ 9,195.08 | $ 1,000.67 | ||||||||
| US and Europe | $ 4,168.87 | $ 650.90 | ||||||||
| US and Europe | $ 885.24 | $ 323.98 | ||||||||
| Asia | $ 3,222.21 | $ 760.28 | ||||||||
| Africa | $ 3,185.18 | $ 455.46 | ||||||||
| Africa | $ 5,050.98 | $ 618.33 | ||||||||
| Africa | $ 306.08 | $ 275.31 | ||||||||
| Africa | $ 9,598.98 | $ 613.29 | ||||||||
| Africa | $ 10,338.80 | $ 979.85 | ||||||||
| Asia | $ 7,350.61 | $ 271.99 | ||||||||
| Africa | $ 7,506.47 | $ 408.01 | ||||||||
| Africa | $ 1,939.78 | $ 413.94 | ||||||||
| US and Europe | $ 7,692.22 | $ 1,015.87 | ||||||||
| US and Europe | $ 1,060.49 | $ 607.34 | ||||||||
| Asia | $ 738.51 | $ 431.47 | ||||||||
| Africa | $ 8,174.84 | $ 206.65 | ||||||||
| Africa | $ 4,368.81 | $ 203.38 | ||||||||
| Africa | $ 1,292.52 | $ 123.11 | ||||||||
| US and Europe | $ 2,210.75 | $ 465.53 | ||||||||
| US and Europe | $ 4,240.74 | $ 737.07 | ||||||||
| Africa | $ 5,927.04 | $ 501.24 | ||||||||
| Africa | $ 2,597.35 | $ 489.99 | ||||||||
| Africa | $ 9,549.49 | $ 835.02 | ||||||||
| Africa | $ 3,931.33 | $ 191.42 | ||||||||
| Africa | $ 8,578.80 | $ 670.24 | ||||||||
| US and Europe | $ 1,946.14 | $ 273.51 | ||||||||
| Asia | $ 9,021.02 | $ 402.06 | ||||||||
| Asia | $ 5,575.67 | $ 148.33 | ||||||||
| US and Europe | $ 1,193.07 | $ 148.13 | ||||||||
| Africa | $ 10,340.53 | $ 250.08 | ||||||||
| Africa | $ 5,512.77 | $ 542.62 | ||||||||
| Asia | $ 2,556.00 | $ 824.13 | ||||||||
| Africa | $ 10,157.81 | $ 508.17 | ||||||||
| Asia | $ 8,921.52 | $ 259.33 | ||||||||
| US and Europe | $ 10,494.44 | $ 565.43 | ||||||||
| Asia | $ 7,007.77 | $ 765.69 | ||||||||
| Asia | $ 4,811.04 | $ 193.17 | ||||||||
| Africa | $ 8,657.83 | $ 171.60 | ||||||||
| Asia | $ 8,204.32 | $ 278.75 | ||||||||
| Africa | $ 4,246.88 | $ 644.52 |
Exercise 3: 1. Using the SUMIF function, list the total Revenue and Expenses for the three regions in the table provided, Columns E - G. 2. Using the Averageif function, list the average Revenue and Expenses for the three regions in the table provided. 3. Using the calculated data, Make a chart presenting total and average Revenue and Expenses for the three regions. 4. Use the textbox to describe in a couple of paragraphs the meaning of the results obtained for Exercise 3. *Keep answers for Exercise 3 in this tab. Total Points: 40
Describe the meaning of the results obtained for Exercise 3 in at least 3 paragraphs (15 points).