Question
The heights (in inches) and weights (in pounds) of 25 baseball players are given below. Use Excel to find the best fit linear regression equation, where height is the explanatory variable. Round the slope and intercept to two decimal places.
Height Weight
71 186
72 211
73 220
70 165
72 180
72 195
70 175
74 202
78 240
71 170
74 180
73 185
76 257
77 215
76 287
77 220
73 200
76 223
76 200
70 220
75 215
71 195
77 194
75 195
75 225
Question
An economist is studying the link between the total value of a country’s exports and that country’s gross domestic product, or GDP. The economist recorded the GDP and Export value (in millions of $’s) for 30 nations for the same fiscal year. This sample data is provided below.
GDP Exports
225274 214010
297106 205300
1470543 189700
511685 188300
930808 184300
261974 180500
542857 152000
331360 151100
703318 148400
269115 142900
154027 128970
101848 125927
271392 104968
97980 88546
181876 93763
266641 82414
139535 77731
76381 74824
212411 62118
169385 61143
594857 65205
144020 57241
353487 55861
99688 55691
155857 53762
137955 55400
164110 46322
422231 45940
149899 43284
257349 37922
Question
In the following table, the age (in years) of the respondents is given as the x value, and the earnings (in thousands of dollars) of the respondents are given as the y value. Use Excel to find the best fit linear regression equation in thousands of dollars. Round the slope and intercept to three decimal places.
x y
21 42.136
22 24.900
22 13.884
24 29.597
24 30.306
25 42.000
25 40.257
27 38.081
27 29.434
30 50.188
31 38.000
32 22.776
32 45.000
33 52.000
34 39.500
38 60.000
40 51.844
40 39.575
42 57.824
42 42.346
43 35.214
43 42.388
43 41.962
44 42.388
45 45.000
45 40.500
46 46.193
47 48.853
48 52.000
48 52.884
49 36.480
49 40.069
50 46.630
50 40.308
51 20.103
53 42.384
54 30.995
55 56.657
56 42.374
56 52.368
57 69.000
57 64.748
57 52.884
58 42.398
59 40.000
Question
A market researcher looked at the quarterly sales revenue for a large e-commerce store and for a large brick-and-mortar retailer over the same period. The researcher recorded the revenue in millions of dollars for 30 quarters. The data are provided below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
E-Commerce Brick-and-mortar
1074 13.11
1155 13.08
1476 12.9
1548 13.77
1800 13.49
1977 13.83
2057 13.89
1955 13.86
1884 13.86
2193 12.9
2186 13.4
2301 12.72
2280 13.38
2457 12.86
2899 12.46
2663 12.28
3414 12.7
3251 12.83
3602 12.07
3697 12.93
3956 12.09
4349 12.63
4497 12.59
4664 12.46
4497 12.03
4473 11.28
4976 11.55
4853 11.84
5103 11.46
5204 11.91
Question
The table below shows primary school enrollment for a certain country. Here, x represents the number of years after 1820, and y represents the enrollment percentage. Use Excel to find the best fit linear regression equation. Round the slope and intercept to two decimal places.
x y
0 0.1
5 0.1
10 0.1
15 0.2
20 0.2
25 0.3
30 0.4
35 0.5
40 0.6
45 1.1
50 1.5
55 3.0
60 4.5
65 5.5
70 6.1
75 6.8
80 7.0
85 8.0
90 9.3
95 10.7
100 12.4
105 14.1
110 16.6
115 17.5
120 19.7
125 19.4
130 32.7
135 40.9
140 47.6
145 57.8
150 57.0
155 61.7
160 63.2
165 75.0
170 76.5
175 96.0
180 92.0
185 100.0
190 100.0
Question
The table below contains the geographic latitudes, x, and average January temperatures, y, of 20 cities. Use Excel to find the best fit linear regression equation. Round the slope and intercept to two decimal places.
x y
46 23
32 60
39 40
33 59
38 57
40 33
42 33
30 64
34 56
41 39
36 49
39 54
47 20
26 76
45 25
31 62
39 42
43 31
37 55
41 31
Question
A government lobby that supports government regulation of the snack industry is looking into snack foods. Looking at a sample of 20 unhealthy snacks (e.g., sweets) they recorded the typical portion size in ounces and the calories per ounce of each snack. This data has been included below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
oz/portion cal/oz
0.91 274.48
0.92 134.03
0.95 146.06
0.93 128.22
2.01 84.79
2.51 108.79
2.01 117.65
0.77 104.97
0.90 118.18
1.13 109.69
3.72 49.35
3.28 113.04
3.34 77.55
1.00 80.46
1.10 155.36
1.59 110.94
4.08 36.57
1.40 136.39
2.71 108.94
1.21 145.03
Question
Jorge is an economist trying to understand whether there is a strong link between CEO compensation and corporate revenue. He gathered data including the CEO compensation for 30 randomly selected corporations for a particular year as well as the corporate revenue of those corporations for the same year. The data Jorge gathered are provided in the accompanying data table. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
CEO Compensation ($) Corporate Revenue (million $)
14215830 20101
14499807 28266
15268679 18524
14476928 28738
15083546 52884
15237297 117162
13881835 23704
13771160 33749
14269205 62478
13025536 44150
12793113 18347
12981100 31891
12682976 20980
13475291 17324
12433901 220088
12972799 29532
12580828 62901
12099198 21757
11965940 20469
11945915 20012
12393340 18356
11860228 22915
11109548 21577
11606923 21132
10978619 19258
11457940 21204
10774262 127285
10357350 18836
10621145 35626
10238177 155104
Solution
Question
The heights (in inches) and weights (in pounds) of 25 baseball players are given below. Use Excel to find the best fit linear regression equation, where height is the explanatory variable. Round the slope and intercept to two decimal places.
Height Weight
71 186
72 211
73 220
70 165
72 180
72 195
70 175
74 202
78 240
71 170
74 180
73 185
76 257
77 215
76 287
77 220
73 200
76 223
76 200
70 220
75 215
71 195
77 194
75 195
75 225
ANS: yˆ=6.53x−275.47……………..please follow the link below to purchase the solution at $4
