During the pandemic, the education department tested the effectiveness of modules in learning basic numbers. Twenty students were tested before and after using the module. The score shows below. What can you conclude from the given data?

During the pandemic, the education department tested the effectiveness of modules in learning basic numbers. Twenty students were tested before and after using the module. The score shows below. What can you conclude from the given data?

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter9: Sequences, Probability And Counting Theory

Section9.7: Probability

Problem 2SE: What is a sample space?

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What is a sample space?
A researcher wanted to know if an individual’s reaction of the election was impacted by their political party and religious beliefs. Test to see if religious belief and political affiliation affects election reaction. Democrat Republican Independent Religious 10140714ΣX2 = 541 1117181816ΣX2 = 1314 2121121723ΣX2 = 1844 Non Religious 211310174ΣX2 = 1015 2420251825ΣX2 = 2550 2228292822ΣX2 = 3377
Month Machine Defects Human Defects Company loses 1 1539 31 99798 2 1284 29 87804 3 1490 27 93681 4 1355 22 82262 5 1500 35 106968 6 1777 30 107925 7 1716 41 117287 8 1045 29 76868 9 1364 47 106001 10 1516 21 88738 11 1623 37 105830 12 1376 37 88730 13 1327 49 100624 14 1178 50 98857 15 1491 37 102622 16 1667 41 108059 17 1769 34 110054 18 1104 44 91892 19 1196 46 98693 20 1794 29 110530 21 1379 38 96883 22 1448 32 99593 23 1505 32 94564 24 1420 42 105752 25 1475 27 93224 26 1118 34 75398 27 1433 58 113137 28 1589 26 85609 29 1585 32 98498 30 1493 33 101803 31 1124 36 88371 32 1536 28 102419 33 1678 41 117183 34 1723 35 107828 35 1413 30 88032 36 1390 54 117943 Interpret the regression outcomes to validate your regression equation, i.e., Multiple R(Correlation of the Regression Equation), R squared, as well as Adjusted R squared. WITHOUT USING AN EXCEL
Month Machine Defects Human Defects Company loses 1 1539 31 99798 2 1284 29 87804 3 1490 27 93681 4 1355 22 82262 5 1500 35 106968 6 1777 30 107925 7 1716 41 117287 8 1045 29 76868 9 1364 47 106001 10 1516 21 88738 11 1623 37 105830 12 1376 37 88730 13 1327 49 100624 14 1178 50 98857 15 1491 37 102622 16 1667 41 108059 17 1769 34 110054 18 1104 44 91892 19 1196 46 98693 20 1794 29 110530 21 1379 38 96883 22 1448 32 99593 23 1505 32 94564 24 1420 42 105752 25 1475 27 93224 26 1118 34 75398 27 1433 58 113137 28 1589 26 85609 29 1585 32 98498 30 1493 33 101803 31 1124 36 88371 32 1536 28 102419 33 1678 41 117183 34 1723 35 107828 35 1413 30 88032 36 1390 54 117943 Interpret the regression outcomes to validate your regression equation, i.e., Multiple R(Correlation of the Regression Equation), R squared, as well as Adjusted R squared.
Month Machine Defects Human Defects Company loses 1 1539 31 99798 2 1284 29 87804 3 1490 27 93681 4 1355 22 82262 5 1500 35 106968 6 1777 30 107925 7 1716 41 117287 8 1045 29 76868 9 1364 47 106001 10 1516 21 88738 11 1623 37 105830 12 1376 37 88730 13 1327 49 100624 14 1178 50 98857 15 1491 37 102622 16 1667 41 108059 17 1769 34 110054 18 1104 44 91892 19 1196 46 98693 20 1794 29 110530 21 1379 38 96883 22 1448 32 99593 23 1505 32 94564 24 1420 42 105752 25 1475 27 93224 26 1118 34 75398 27 1433 58 113137 28 1589 26 85609 29 1585 32 98498 30 1493 33 101803 31 1124 36 88371 32 1536 28 102419 33 1678 41 117183 34 1723 35 107828 35 1413 30 88032 36 1390 54 117943 1. Formulate a regression equation to show a linear relationship between the variables. (Remember your regression equation should take the form Y = fn (X, ..., etc). Thus, Y = a + b1X1+... + e)
Month Machine Defects Human Defects Company loses 1 1539 31 99798 2 1284 29 87804 3 1490 27 93681 4 1355 22 82262 5 1500 35 106968 6 1777 30 107925 7 1716 41 117287 8 1045 29 76868 9 1364 47 106001 10 1516 21 88738 11 1623 37 105830 12 1376 37 88730 13 1327 49 100624 14 1178 50 98857 15 1491 37 102622 16 1667 41 108059 17 1769 34 110054 18 1104 44 91892 19 1196 46 98693 20 1794 29 110530 21 1379 38 96883 22 1448 32 99593 23 1505 32 94564 24 1420 42 105752 25 1475 27 93224 26 1118 34 75398 27 1433 58 113137 28 1589 26 85609 29 1585 32 98498 30 1493 33 101803 31 1124 36 88371 32 1536 28 102419 33 1678 41 117183 34 1723 35 107828 35 1413 30 88032 36 1390 54 117943 1. Formulate a regression equation to show a linear relationship between the variables. (Remember your regression equation should take the form Y = fn (X, ..., etc). Thus, Y = a + b1X1+... + e) without using an excel
Male Female26,801 21,39217,251 25,0384,624 4,47927,801 18,27024,555 10,6637,767 17,11020,536 10,77916,516 19,98425,601 14,05620,948 18,51912,153 17,70311,382 11,30813,138 17,00723,568 25,14217,874 5,616102 17,63120,292 24,5689,701 16,93722,178 15,53116,189 12,88517,664 30,97022,418 6,5195,993 18,3335,899 6,10424,563 10,00311,655 17,88411,600 12,35514,317 20,13011,649 21,96117,427 13,33914,658 35,76910,205 10,68520,063 9,15415,219 11,99611,846 30,61614,723 20,53517,184 16,2678,686 17,89917,833 20,14113,345 14,90014,770 19,1535,386 11,94719,548 16,55313,755 18,12515,959 30,23816,800 38,61218,987 24,75439,299 33,12517,677 25,55947,062 32,94627,391 20,46511,298 5,18615,815 25,02111,590 14,5586,579 15,67619,395 28,954
Covid-19 Situation Report, Table 4b, represents the number of confirmed Covid 19 cases of top 50affected countries as per the COVID 19 Situation report released by World Health Organization onMay 31, 2020.1 716 078 465 166 148 285 94 858 89 741 84 627 38 571 26 688 16 908 14 70212 531 30 967 148 950 83 384 69 496 55 262 33 896 26 192 23 449 15 09411 468 16 851 405 843 272 830 239 600 232 664 181 482 163 103 148 436 58 18646 257 41 658 37 113 32 203 30 762 24 929 23 672 23 571 19 133 17 01216 638 11 633 11 381 10 858 182 143 44 608 25 773 84 570 34 366 17 224Table 4bPage 5 of 6Determine the following types of averages for the discrete dataset in Table 4b;a) Airthmetic Meanb) Medianc) Mode
Student ID Math Score Project Score Age (years) Sex 001254 52 75 15 M 003256 78 89 15 F 001547 92 82 18 F 012589 91 66 17 M 021475 72 93 14 M 032658 46 76 13 M 009561 68 76 14 F 008654 52 82 12 F 008561 83 75 16 M 003547 45 78 14 F 047452 73 96 14 M 041212 64 79 13 F 032320 41 67 13 F 000258 77 72 15 F 001478 82 75 17 M 019521 59 83 15 M 017451 80 71 17 F 016335 48 76 13 M 002474 57 80 14 F 095844 97 71 18 F 097304 86 86 17 M 090024 75 85 15 F 034702 81 80 16 F 001910 67 74 14 F 006454 86 77 17 M 087478 63 82 13 M 078474 68 79 14 F 000977 54 89 12 M 063010 91 73 18 M 007406 46 77 15 F 025740 93 85 17 M…
Student ID Math Score Project Score Age (years) Sex 001254 52 75 15 M 003256 78 89 15 F 001547 92 82 18 F 012589 91 66 17 M 021475 72 93 14 M 032658 46 76 13 M 009561 68 76 14 F 008654 52 82 12 F 008561 83 75 16 M 003547 45 78 14 F 047452 73 96 14 M 041212 64 79 13 F 032320 41 67 13 F 000258 77 72 15 F 001478 82 75 17 M 019521 59 83 15 M 017451 80 71 17 F 016335 48 76 13 M 002474 57 80 14 F 095844 97 71 18 F 097304 86 86 17 M 090024 75 85 15 F 034702 81 80 16 F 001910 67 74 14 F 006454 86 77 17 M 087478 63 82 13 M 078474 68 79 14 F 000977 54 89 12 M 063010 91 73 18 M 007406 46 77 15 F 025740 93 85 17 M…
Student ID Math Score Project Score Age (years) Sex 001254 52 75 15 M 003256 78 89 15 F 001547 92 82 18 F 012589 91 66 17 M 021475 72 93 14 M 032658 46 76 13 M 009561 68 76 14 F 008654 52 82 12 F 008561 83 75 16 M 003547 45 78 14 F 047452 73 96 14 M 041212 64 79 13 F 032320 41 67 13 F 000258 77 72 15 F 001478 82 75 17 M 019521 59 83 15 M 017451 80 71 17 F 016335 48 76 13 M 002474 57 80 14 F 095844 97 71 18 F 097304 86 86 17 M 090024 75 85 15 F 034702 81 80 16 F 001910 67 74 14 F 006454 86 77 17 M 087478 63 82 13 M 078474 68 79 14 F 000977 54 89 12 M 063010 91 73 18 M 007406 46 77 15 F 025740 93 85 17 M…
495745947949979437 x 7826736386487342622 - 1000000 x 634634662354 + 8766348764410939824383658 x 8483 + 636536425195805057509 + 64658659875963