Equate the Regression Line in the Form ? = ? + ??.New CasesNew Deaths17654109758914959693758104726135391776819523419068205211152413914531461912402048137205881895112163141357691862641783742178201797541949531581501173942245951169711849482109712103801658581583671266681590551894611941521790701690521235651345114173468202226196012192881685213917118453174496190115722402391888202288614141615572222697226514629214221132920374206747178320245215304519343942327651335652668728861737496345788750007248996354048443711438718529021710313799930775739801945867206666478773569838549595109475111001616929656128106

The least square regression line is given by, ŷ = bx+a Where b=…

Answered: Equate the Regression Line in the Form…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A study was done to look at the relationship between number of vacation days employees take each year and the number of sick days they take each year. The results of the survey are shown below. Vacation Days 5 15 13 3 9 0 3 7 7 14 4 Sick Days 5 5 1 5 4 9 9 6 5 3 9 Use the model to predict the number of sick days taken for an employee who took 3 vacation days this year.Sick Days = ? (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: As x goes up, y goes down. The slope has no practical meaning since a negative number cannot occur with vacation days and sick days. For every additional vacation day taken, employees tend to take on average 0.40 fewer sick days. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. If an employee takes no vacation days, then that employee will take 8 sick days. The average number of sick days is…
Suppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87
Interpret the Regression Line Model New Cases New Deaths 1765 4 1097 5 891 4 959 6 937 58 1047 26 1353 9 1776 8 1952 34 1906 8 2052 11 1524 139 1453 146 1912 40 2048 137 2058 8 1895 11 2163 14 1357 69 1862 64 1783 74 2178 20 1797 54 1949 53 1581 50 1173 94 2245 95 1169 71 1849 48 2109 71 2103 80 1658 58 1583 67 1266 68 1590 55 1894 61 1941 52 1790 70 1690 52 1235 65 1345 114 1734 68 2022 26 1960 12 1928 8 1685 2 1391 7 1184 53 1744 96 1901 157 2240 239 1888 20 2288 6 1414 16 1557 22 2269 72 2651 46 2921 42 2113 29 2037 4 2067 47 1783 20 2452 15 3045 19 3439 42 3276 51 3356 5 2668 7 2886 17 3749 63 4578 87 5000 72 4899 63 5404 8 4437 11 4387 18 5290 21 7103 13 7999 30 7757 39 8019 4 5867 20 6666 47 8773 56 9838 54 9595 10 9475 11 10016 16 9296 5 6128 106
The table shows the national expenditures for health care in billions, in a country for the selected years from 1990 to 2020. Given the projection cost for the year 2002, identify the type of regression point. Year Exprenditures ($billions) 1991 1020 1994 1356 1998 1984 2004 2984 2009 3374 2016 4765 2020 5937 Interpolation Extrapolation Neither Both
Please give the excel formula or spreadsheet.
a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
Below is data for two variables, X and Y. Answer the questions that follow. X Y X-MX Y-MY (X-MX)2 (Y-MY)2 (X-MX)(Y-MY) 3 3 -2 -1 4 1 2 4 3 -1 -1 1 1 ___ 6 4 1 ___ 1 0 0 7 6 2 2 ___ 4 4 r = ____
Outside Sr # Tempera (Number Sales X(outsid Y(sales) X*2 Y*2 Y=-5 e ture of Air tempera (Degrees Conditio ture) F) ning units sold) 68 3 68 3 4624 204 1.636 72 72 5 5184 25 360 4.883 78 7 3 78 7. 6084 49 546 9.754 81 12 4 81 12 6561 144 972 12.19 84 15 84 15 7056 225 1260 14.62 86 16 6 86 16 7396 256 1376 16.25 89 22 89 22 7921 484 1958 18.68 91 18 91 18 8281 324 1638 20.31 93 19 9 93 19 8649 361 1767 21.93 94 26 10 94 26 8836 676 2444 22.74 836 143 7059 2553 12525 143 sum Y= Plot a scatter diagram for the data provided on the table above and the linear regression line calculated in topic (b). Consider that: Y: number of air conditioning units sold X: outside temperature (degrees F) rds English (U.S.) Text Predictions: On acer
Here is a set of data. 78 111 135 261 299 398 444 496 662 733 769 818 836 868 Identify the 5 number summary (min, Q1, median, Q3, max) , , , ,
The following data is the number of tickets sold and the jackpot value for the Mega Millions lottery. The jackpot value is in millions of dollars and the number of tickets sold is in millions. Jackpot value 334 127 300 227 202 180 164 145 255 Number of tickets sold 54 16 41 27 23 18 18 16 26 r= 0.947 tickets sold -10.87 +0.17 (jackpot value) Which is the independent variable and which is the dependent variable? X= independent variable = Y= dependent variable Interpret ². Interpret the slope. Predict the number of tickets sold when the jackpot value is 500 million dollars. Would you feel comfortable using the model for this value? Why or why not.
Solve.

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New Cases	New Deaths
1765	4
1097	5
891	4
959	6
937	58
1047	26
1353	9
1776	8
1952	34
1906	8
2052	11
1524	139
1453	146
1912	40
2048	137
2058	8
1895	11
2163	14
1357	69
1862	64
1783	74
2178	20
1797	54
1949	53
1581	50
1173	94
2245	95
1169	71
1849	48
2109	71
2103	80
1658	58
1583	67
1266	68
1590	55
1894	61
1941	52
1790	70
1690	52
1235	65
1345	114
1734	68
2022	26
1960	12
1928	8
1685	2
1391	7
1184	53
1744	96
1901	157
2240	239
1888	20
2288	6
1414	16
1557	22
2269	72
2651	46
2921	42
2113	29
2037	4
2067	47
1783	20
2452	15
3045	19
3439	42
3276	51
3356	5
2668	7
2886	17
3749	63
4578	87
5000	72
4899	63
5404	8
4437	11
4387	18
5290	21
7103	13
7999	30
7757	39
8019	4
5867	20
6666	47
8773	56
9838	54
9595	10
9475	11
10016	16
9296	5
6128	106