. Prepare a crosstabulation of the data on Industry (rows) and Brand Revenue ($ billions). Use class intervals of 25 starting at 0 for Brand Revenue ($billions) b. Prepare a frequency distribution for the data on Brand revenue ($ billions). c. What conclusions can you draw about the type of industry and the brand revenue? d. Prepare a crosstabulation of the data on Industry (rows) and the 1-year Value change (%). Use class intervals of 20 starting at -60 for 1 year Value Change (%). e. Prepare a frequency distribution for the data on 1 -
. Prepare a crosstabulation of the data on Industry (rows) and Brand Revenue ($ billions). Use class intervals of 25 starting at 0 for Brand Revenue ($billions) b. Prepare a frequency distribution for the data on Brand revenue ($ billions). c. What conclusions can you draw about the type of industry and the brand revenue? d. Prepare a crosstabulation of the data on Industry (rows) and the 1-year Value change (%). Use class intervals of 20 starting at -60 for 1 year Value Change (%). e. Prepare a frequency distribution for the data on 1 -
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
a. Prepare a crosstabulation of the data on Industry (rows) and Brand Revenue |
($ billions). Use class intervals of 25 starting at 0 for Brand Revenue ($billions) |
b. Prepare a frequency distribution for the data on Brand revenue ($ billions). |
c. What conclusions can you draw about the type of industry and the brand revenue? |
d. Prepare a crosstabulation of the data on Industry (rows) and the 1-year Value change |
(%). Use class intervals of 20 starting at -60 for 1 year Value Change (%). |
e. Prepare a frequency distribution for the data on 1 - year Value Change (%). |
f. What conclusions can you draw about the type of industry and the 1-year change in |
value? |
Show steps in Excel.
Brand | Industry | Brand Value ($ billions) | 1-Yr Value Change (%) | Brand Revenue ($ billions) |
Accenture | Other | 9.7 | 10 | 30.4 |
Adidas | Other | 8.4 | 23 | 14.5 |
Allianz | Financial Services | 6.9 | 5 | 130.8 |
Amazon.Com | Technology | 14.7 | 44 | 60.6 |
American Express | Financial Services | 18 | 5 | 33.8 |
Audi | Automotive & Luxury | 10.9 | 1 | 55.2 |
AXA | Financial Services | 5.6 | 10 | 149.3 |
Bank of America | Financial Services | 7.7 | -9 | 83.3 |
Boeing | Other | 6.4 | 12 | 81.7 |
Burberry | Automotive & Luxury | 5.5 | 13 | 3 |
Canon | Technology | 8.7 | -11 | 41.8 |
Caterpillar | Other | 8.5 | 21 | 65.9 |
Chanel | Automotive & Luxury | 7 | 13 | 4.4 |
Chase | Financial Services | 6.3 | -9 | 56.8 |
Coach | Automotive & Luxury | 10.5 | 1 | 5.1 |
Colgate | Consumer Packaged Goods | 7.9 | 7 | 3.9 |
Credit Suisse | Financial Services | 5.7 | -9 | 42 |
Danone | Consumer Packaged Goods | 11.1 | 13 | 13.3 |
Dell | Technology | 6.4 | -23 | 56.9 |
Ebay | Technology | 8.5 | 14 | 6.3 |
Ericsson | Technology | 5.9 | -35 | 34.6 |
ESPN | Other | 12.9 | 12 | 10.4 |
Estee Lauder | Consumer Packaged Goods | 5.4 | 15 | 4.4 |
Technology | 13.7 | 4 | 5.1 | |
FedEx | Other | 5.8 | 10 | 44.3 |
Ford | Automotive & Luxury | 10.6 | 34 | 130 |
Fox | Other | 10.2 | 20 | 11.7 |
Frito-Lay | Consumer Packaged Goods | 11.6 | 6 | 11.1 |
General Electric | Other | 34.2 | 2 | 132.1 |
Gillette | Consumer Packaged Goods | 18.3 | 9 | 8 |
Goldman Sachs | Financial Services | 6.8 | -15 | 41.7 |
Technology | 47.3 | 26 | 43.5 | |
Gucci | Automotive & Luxury | 12.1 | 1 | 4.7 |
H&M | Other | 16.1 | 12 | 18.3 |
Heineken | Other | 7 | 7 | 6 |
Heinz | Consumer Packaged Goods | 5.6 | 2 | 4.4 |
Hermès | Automotive & Luxury | 9.3 | 20 | 4.5 |
Hewlett-Packard | Technology | 15.3 | -16 | 119.9 |
Home Depot | Other | 10.1 | 12 | 74.8 |
HSBC | Financial Services | 15.2 | 0 | 104.9 |
Hyundai | Automotive & Luxury | 6.5 | 21 | 49.7 |
IBM | Technology | 50.7 | 5 | 104.5 |
IKEA | Other | 11.5 | 5 | 35.5 |
ING | Financial Services | 5.7 | 8 | 118.7 |
Intel | Technology | 30.9 | -4 | 53.3 |
J.P. Morgan | Financial Services | 9.1 | -30 | 43.1 |
John Deere | Other | 6.4 | 14 | 36.2 |
Kellogg's | Consumer Packaged Goods | 8.7 | -6 | 7.1 |
Kraft | Consumer Packaged Goods | 9.1 | -10 | 7.1 |
Lancome | Consumer Packaged Goods | 6.2 | 13 | 4 |
Lexus | Automotive & Luxury | 7 | 1 | 18.7 |
L'Oréal | Consumer Packaged Goods | 16.9 | 16 | 10.6 |
Louis Vuitton | Automotive & Luxury | 28.4 | 16 | 9.4 |
Marlboro | Other | 16.6 | 9 | 23.6 |
Mastercard | Financial Services | 7.4 | 8 | 7.4 |
McDonald's | Other | 39.4 | 5 | 88.3 |
Microsoft | Technology | 56.7 | 4 | 77.8 |
MTV | Other | 5.6 | -7 | 3.1 |
Nestle | Consumer Packaged Goods | 11.8 | 18 | 11.3 |
NIKE | Other | 18.2 | 14 | 23.7 |
Nintendo | Technology | 8 | -39 | 7.6 |
Nissan | Automotive & Luxury | 6.9 | 17 | 108.5 |
Nokia | Technology | 7 | -55 | 38.8 |
Pampers | Consumer Packaged Goods | 9.6 | 12 | 10.4 |
Philips | Other | 7.1 | 14 | 31.9 |
Porsche | Automotive & Luxury | 5.7 | 16 | 17.8 |
Prada | Automotive & Luxury | 7.1 | 23 | 3.4 |
Ralph Lauren | Other | 6.4 | 28 | 6.4 |
Rolex | Automotive & Luxury | 7.4 | 14 | 4.5 |
Santander | Financial Services | 6 | -2 | 57.3 |
SAP | Technology | 19.6 | 28 | 20.3 |
Siemens | Other | 13.7 | 1 | 100.6 |
Sony | Technology | 6.6 | -20 | 69.5 |
Starbucks | Other | 6.9 | 9 | 13 |
Subway | Other | 5.7 | 17 | 18.1 |
Thomson Reuters | Other | 9.6 | -10 | 7.2 |
UPS | Other | 10.2 | 13 | 54.1 |
Verizon | Other | 19.3 | 0 | 115.8 |
Visa | Financial Services | 14.2 | 12 | 10.4 |
Volkswagen | Automotive & Luxury | 8.1 | 16 | 145.7 |
Wells Fargo | Financial Services | 9 | -14 | 91.2 |
Zara | Other | 9.4 | 11 | 13.5 |
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