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2.1: This is what too many numbers looks like

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    7891
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    Let’s say you wanted to know how happy people are. So, you ask thousands of people on the street how happy they are. You let them pick any number they want from negative infinity to positive infinity. Then you record all the numbers. Now what?

    Well, how about you look at the numbers and see if that helps you determine anything about how happy people are. What could the numbers look like. Perhaps something like this:

    73 594 -22 -20 -547 162 -90 312 235 -511
    -337 85 552 377 241 -382 241 -439 264 -292
    -136 -262 432 835 73 -180 -93 218 597 419
    -500 -120 588 -96 -412 502 1058 761 549 -320
    14 -869 338 935 531 339 83 37 820 544
    50 -397 203 -374 -186 518 530 1320 816 1293
    580 -741 -102 -56 933 -228 -347 656 162 714
    440 569 -431 557 -502 -331 -281 73 311 459
    -143 -348 136 -624 55 -790 374 -988 -1102 -408
    -666 671 660 452 1299 717 369 158 679 411
    -593 -364 115 379 56 -440 505 -370 -102 -1020
    610 -86 -181 -143 75 -188 502 606 443 74
    181 -355 40 551 -362 414 -307 415 -930 -302
    1416 -387 437 -126 -407 28 466 -25 -413 -286
    106 257 459 703 3 1592 1042 -124 102 -578
    550 -605 -41 167 -581 830 -17 200 98 472
    242 -30 94 -619 -885 424 320 241 193 121
    -373 -478 -398 1035 425 -199 -350 189 -394 346
    -161 -355 108 -685 -668 -667 893 -623 19 879
    -430 119 830 -236 -527 61 313 265 453 -565
    -523 9 -413 -705 -527 237 -341 80 349 891
    181 555 371 -623 -107 859 -673 855 4 117
    -1225 317 279 266 24 -387 368 567 -717 717
    -110 706 -40 -836 -882 48 307 1150 -917 -236
    -669 -401 -274 -465 -178 104 517 635 86 186
    -357 356 932 118 -51 62 -111 -154 -409 852
    -91 -568 640 -48 -349 -481 511 -544 254 -641
    654 -127 -563 -340 30 -293 -100 292 220 41
    312 640 -628 335 -808 105 77 -674 108 -1177
    -804 -318 608 954 -350 606 -394 -68 -226 161
    -580 174 622 -433 -758 -49 949 496 802 -271
    745 184 -41 281 -318 -323 634 -53 -307 446
    245 368 163 -489 -124 -258 -463 357 -465 -321
    628 1055 -11 -177 -28 139 -531 134 -400 -182
    -298 153 -206 946 534 295 543 350 184 -311
    1109 -174 1169 -175 88 804 -555 -269 -376 1199
    -463 1078 -384 -804 2 -29 219 -467 375 503
    1717 264 -177 -222 1125 -738 569 -335 581 364
    -36 -523 847 -1189 -379 -704 -654 51 -136 303
    609 -200 675 286 353 67 -993 -181 1198 -508
    77 58 -53 -510 -343 657 1303 -300 804 -376
    421 73 -165 -238 409 470 648 127 347 -296
    659 280 1397 -715 979 -793 565 -102 510 333
    -848 571 -297 630 286 -512 275 468 -314 -246
    -212 603 -152 -474 428 -315 -38 -53 -324 -225
    -46 -89 316 341 516 -655 613 249 334 94
    -66 -688 101 -128 -422 424 326 -287 417 -605
    357 -959 -149 387 -39 -104 -596 55 -25 -26
    -533 -667 280 863 215 -182 397 333 -56 36
    -118 -329 44 -1 354 -545 630 460 458 30

    Now, what are you going to with that big pile of numbers? Look at it all day long? When you deal with data, it will deal so many numbers to you that you will be overwhelmed by them. That is why we need ways to describe the data in a more manageable fashion.

    The complete description of the data is always the data itself. Descriptive statistics and other tools for describing data go one step further to summarize aspects of the data. Summaries are a way to compress the important bits of a thing down to a useful and manageable tidbit. It’s like telling your friends why they should watch a movie: you don’t replay the entire movie for them, instead you hit the highlights. Summarizing the data is just like a movie preview, only for data.


    2.1: This is what too many numbers looks like is shared under a CC BY-SA 4.0 license and was authored, remixed, and/or curated by Matthew J. C. Crump via source content that was edited to conform to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.

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