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Using Microsoft Excel to Visualize Climate Data. “Data Mining”. Computers have allowed scientists to collect, save, and share vast amounts of data. New fields such as “data mining” and “bioinformatics” use data collected by other scientists to conduct research and find patterns. - PowerPoint PPT Presentation
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Using Microsoft Excel to Visualize Climate Data
“Data Mining”• Computers have allowed
scientists to collect, save, and share vast amounts of data.
• New fields such as “data mining” and “bioinformatics” use data collected by other scientists to conduct research and find patterns.
Communicating information with graphsMean Background Site 2
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3781.917 5229.639 6274.806 5541.806 4962.9502 4715 34713 12245 39971 17971 16984 24376.8 304714848.639 4028.139 3816.722 3799.611 4016.4556 3816 22120 31837 11513 13584 13063 18423.4 23029
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9002 7064.444 6879.167 15243.111 9306.2278 8841 27121 28543 20049 27986 23805 25500.8 318766738.25 7552.972 6457.361 8695.972 7114.2166 6759 23026 34166 28179 24775 22656 26560.4 33201
5013.028 3043.556 4028.25 3085.806 3879.2002 3685 11406 6387 11126 6309 11588 9363.2 11704
2846.389 2813.806 2656.361 3207.833 2933.139 2786 5969 9819 67377508.3333
33 93855784.917 14809.361 7433.75 9723.944 8888.4166 8444 35653 19162 26461 20421 22477 24834.8 310447133.528 6776.861 6271.833 7619.333 6861.0166 6518 15245 23251 18585 19027 237843803.706 3749.545 4271.951 4116.07 3927.2446 3731 10444 18190 11909 10640 7801 11796.8 147463396.315 3428.441 4509.252 4542.706 3841.6072 3650 7741 6492 8472 7718 6111 7306.8 91341616.965 1794.706 1587.909 1725.105 1662.179 1579 4742 4819 4454 4445 3954 4482.8 56041579.154 2002.888 2012.224 1629.51 1754.2684 1667 4291 3070 2658 2337 3089 3861
2109.72 2274.035 2379.713 2205.336 2200.3804 2090 4604 4726 3959 3699 4660 4329.6 54125883.28 7715.503 6587.28 6077.86 6928.4852 6582 21525 22254 20309 14571 42573 24246.4 30308
6199.091 7404.791 7043.391 7814.118 7204.9946 6845 16654 19796 15383 16412 17061.25 213278067.845 11702.673 11003.836 9127.873 9545.4982 9068 14082 17124 17150 16906 16315.5 20394
14475.845 12849.936 11730.727 13569.48213373.343
4 12705 30653 24355 28824 28428 25166 27485.2 34357
16852.627 12499.073 14901.364 12021.43613861.463
6 13168 22204 33350 3060528719.666
67 359004849.227 4177.636 5467.809 4036.036 4850.827 4608 25915 13785 20005 21179 18671 19911 248893733.918 4606.991 5587.309 3704.2 4438.5 4217 20392 16084 13320 14384 22413 17318.6 216484429.245 4965.827 4554.045 5439.736 4745.0216 4508 13865 12055 10084 12924 14071 12599.8 157506631.618 5429.391 4839.364 5191.118 5561.6072 5284 15362 13168 11540 10987 11678 12547 15684
7845.9 6909.855 8500.127 10410.636 8103.3308 7698 39774 30564 24224 30048 21075 29137 364218868.418 8822.964 6337.155 7300.509 7761.3202 7373 18372 17871 16612 19956 18202.75 227534052.909 3884.564 3514.755 3192.136 3614.9364 3434 9794 11044 10425 8465 8598 9665.2 120823763.291 3825.973 3589.945 3621.336 3746.2326 3559 9592 12523 11663 11254 13860 11778.4 147233863.627 4692.382 4573.409 4047.691 4444.6072 4222 10517 7827 6151 7404 7974.75 99684021.809 5794.682 4048.318 3276.509 4219.669 4009 12811 14373 17235 9398 14423 13648 170603424.236 5680.045 3922.509 3359.009 3946.187 3749 21586 21945 19851 18955 17522 19971.8 24965
8730.6 6492.636 7153.4 6687.164 7154.26 6797 45909 45160 43105 33393 27688 39051 488146055.018 7955.6 5900.173 7772.664 6860.3856 6517 27270 16749 27374 14007 21350 26688
8812.836 10822.936 8928.645 10622.35510324.787
2 9809 21773 22677 26675 21500 19379 22400.8 28001
11680.073 12677.809 11022.955 10488.37311210.407
4 10650 27338 35344 26491 23863 24776 27562.4 34453
10051.745 13873.109 10653.727 16437.52711772.105
2 11183 26313 36513 65535 52769 36163 43458.6 543235950.036 4236.809 6621.627 4460.291 5574.458 5296 12512 9765 13172 10570 11504.75 14381
4584.6 3602.291 5342.327 4851.464 4641.7292 4410 10364 10764 8105 7029 7819 8816.2 110204174.536 4287.055 4155.573 4608.791 4169.4364 3961 9555 12702 10628 13498 17161 12708.8 158863862.527 3911.6 4648.345 6101.464 4570.3618 4342 9338 10801 11330 11032 10751 10650.4 13313
9013.2 11353.455 9975.882 12557.411001.658
4 10452 36066 31564 30605 25902 23095 29446.4 368088225.027 8867.355 8872.855 8086.527 8697.9256 8263 19134 16772 17153 13375 11173 15521.4 194028272.845 6358.364 7618.691 8468.373 7495.0746 7120 27666 34109 23336 30646 24098 27971 34964
18002.309 15536.209 19229.936 15174.39118570.321
8 17642 45961 36331 31673 55353 52128 44289.2 553626738.836 7886.109 6792.691 7181.391 7513.229 7138 28396 31920 23805 25014 23797 26586.4 332339333.736 8516.282 8984.555 9073.582 9490.1674 9016 26976 31249 32723 26839 32489 30055.2 37569
12181.273 15009.009 12447.018 7283.69111383.054
6 10814 32952 29892 31543 26778 21736 28580.2 35725
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6 13120 27946 26700 3762630757.333
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2 16258 33141 33258 32076 31274 29113 31772.4 3971617140.709 18915.164 19580.355 18534.664 17799.453 16909 34319 42232 43776 39801 38912 39808 4976010123.964 18217.045 16346.827 13513.409 14364.598 13646 33331 37697 37947 36589 38238 36760.4 45951
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8 16479 29784 37168 30698 29010 26089 30549.8 38187
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8 9798 29796 21477 35969 35504 30686.5 3835811703.764 14932.845 13077.636 11725.5 12413.778 11793 35237 35278 54225 50115 49384 44847.8 56060
8753.918 9575.364 10482.764 7960.764 8976.1366 8527 17289 27474 38314 23598 32109 27756.8 346968197.255 7648.345 7924.827 7861.318 8377.5036 7959 30966 20254 20979 16879 19778 21771.2 27214
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2 11787 33173 32136 39339 42535 40353 37507.2 4688410608.055 9072.809 8947.827 9770.427 9600.2546 9120 24369 32684 31490 26699 23299 27708.2 34635
A small datasetA graph representing the averages of the values that the scientist wants you to know about
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Which is easier to understand?
Today we will use some publicly available data about weather and climate
Sources for Climate Data:• Climate Reanalyzer cci-
reanalyzer.org (includes many public datasets)
• Rutgers University Global Snow Lab
• Global Historical Climate Network
• U.S. Historical Climatology Network
• Goddard Institute for Space Studies
• Scripps CO2 Program• …and many more!
Today we will use some publicly available data about weather and climate
One example of a very complex data visualization.Data can be beautiful, too!
But there is public data for many different topics, and even online tools to help you explore
Topics• Infectious Disease
Outbreaks• World Economies• Broadband
performance• Life Expectancy• Standardized Test
Performance
Tools• Google Public Data
Explorer• NorthWest Public
Health Observatory• National Center for
Education Statistics
“47.3% of all statistics are made up on the spot.”
-Steven Wright
Graphs in the media: People will use graphs to mislead you
These plots show the exact same information, what makes them appear different?
Do you come away with the same impression from both graphs? Why or why not?
People will use graphs to mislead you
These plots show the exact same information, what makes them appear different?
Do you come away with the same impression from both graphs? Why or why not?
Visual effects can be misleading
These plots show the exact same information, what makes them appear different?
Do you come away with the same impression from both graphs? Why or why not?
Being a “savvy consumer” of data: Questions to ask of graphs you see in daily life
• Who is telling me this? Could they benefit from me interpreting the data a certain way?
• Where did the numbers come from?– Often companies will pay for research studies. These
researchers may be pressured to produce data that is good for the company’s “bottom line.”
• Did they use an appropriate graph to display the data?– Is there information they are leaving out by not using the
appropriate graph?– Is there other information they aren’t telling you?
Visual effects can be misleading
It can be tempting to use “cool” visual effects in your graphs, but often these impair the readers’ ability to understand the plot.
People have difficulty distinguishing and remembering >8 colors in one graph.
The colors in this graph do not actually mean anything about the data.
In trying to make the graph colorful, the creator has caused confusion. This can also be misleading if people attempt to attach meaning to the different colors.
