Team | League | Wins | ERA | BA | HR | SB | Errors | Built | Size | Attendance | Payroll | ||||||||||||||
|
NL | 57 | 5.00 | 0.242 |
|
87 | 127 | 2001 | 38496 | 1.61 | 34.9 | ||||||||||||||
|
NL | 90 | 3.39 | 0.246 |
|
124 | 72 | 2004 | 42445 | 2.13 | 37.8 | ||||||||||||||
|
AL | 81 | 3.56 | 0.256 |
|
156 | 99 | 1966 | 34077 | 1.42 | 51.7 | ||||||||||||||
|
AL | 90 | 3.93 |
|
|
|
105 | 1994 | 49115 | 2.51 | 55.3 | ||||||||||||||
|
NL | 80 | 4.08 | 0.254 |
|
92 | 123 | 1987 | 36331 | 1.54 | 55.6 | ||||||||||||||
|
NL | 65 | 4.81 | 0.250 |
|
86 | 102 | 1998 | 49033 | 2.06 | 60.7 | ||||||||||||||
|
AL | 69 | 4.30 | 0.248 |
|
91 | 110 | 1994 | 43345 | 1.39 | 61.2 | ||||||||||||||
|
NL | 69 | 4.13 | 0.250 |
|
110 | 127 | 2008 | 41888 | 1.83 | 61.4 | ||||||||||||||
|
AL | 85 | 4.22 | 0.248 |
|
58 | 92 | 1989 | 50516 | 1.63 | 62.7 | ||||||||||||||
|
AL | 96 | 3.78 | 0.247 |
|
172 | 85 | 1990 | 36048 | 1.84 | 71.9 | ||||||||||||||
|
AL | 67 | 4.97 | 0.274 |
|
115 | 121 | 1973 | 40793 | 1.62 | 72.3 | ||||||||||||||
|
NL | 91 | 4.01 | 0.272 | 188 | 93 | 72 | 2003 | 42059 | 2.06 | 72.4 | ||||||||||||||
|
NL | 77 | 4.58 | 0.262 |
|
81 | 101 | 2001 | 42200 | 2.78 | 81.1 | ||||||||||||||
|
AL | 66 | 4.59 | 0.259 |
|
76 | 105 | 1992 | 48876 | 1.73 | 81.6 | ||||||||||||||
|
NL | 83 | 4.14 | 0.263 |
|
99 | 101 | 1995 | 50445 | 2.88 | 84.2 | ||||||||||||||
|
NL | 91 | 3.56 | 0.258 |
|
63 | 126 | 1996 | 50091 | 2.51 | 84.4 | ||||||||||||||
|
NL | 76 | 4.09 | 0.247 |
|
100 | 103 | 2000 | 40950 | 2.33 | 92.4 | ||||||||||||||
|
NL | 86 | 3.57 | 0.263 |
|
79 | 99 | 2006 | 49660 | 3.3 | 93.5 | ||||||||||||||
|
NL | 80 | 4.01 | 0.252 |
|
92 | 98 | 1962 | 56000 | 3.56 | 94.9 | ||||||||||||||
|
AL | 94 | 3.95 |
|
142 | 68 | 78 | 2010 | 40000 | 3.22 | 97.6 | ||||||||||||||
San Francisco Giants |
|
|
|
0.257 | 162 | 55 | 73 | 2000 | 41503 | 3.04 | 97.8 | ||||||||||||||
|
AL | 61 | 3.93 | 0.236 |
|
142 | 110 | 1999 | 47116 | 2.09 | 98.4 | ||||||||||||||
|
AL | 80 | 4.04 | 0.248 |
|
104 | 113 | 1966 | 45050 | 3.25 | 105 | ||||||||||||||
|
AL | 88 | 4.09 | 0.268 |
|
160 | 103 | 1991 | 40615 | 2.19 | 108.3 | ||||||||||||||
|
AL | 81 | 4.30 | 0.268 |
|
69 | 109 | 2000 | 41782 | 2.46 | 122.9 | ||||||||||||||
|
NL | 79 | 3.70 | 0.249 |
|
130 | 87 | 2009 | 45000 | 2.56 | 132.7 | ||||||||||||||
|
NL | 97 | 3.67 | 0.260 |
|
108 | 83 | 2004 | 43647 | 3.65 | 141.9 | ||||||||||||||
|
NL | 75 | 4.18 | 0.257 |
|
55 | 126 | 1914 | 41118 | 3.06 | 146.9 | ||||||||||||||
|
AL | 89 | 4.20 | 0.268 |
|
68 | 111 | 1912 | 39928 | 3.05 | 162.7 | ||||||||||||||
|
AL | 95 | 4.06 | 0.267 |
|
103 | 69 | 2009 | 52325 | 3.77 | 206.3 |
- Can some one help me understand how to conduct this using excel
Team League Wins ERA BA HR SB Errors Built Size Attendance Payroll Pittsburgh Pirates NL 57...
Problem #1: TO SELECT THE MOST ECONOMICAL Wio SHAPE COLUMN ZO FEET IN HEIGHT SUPPORT AH AXIAL LORD OF 370 KIPS using soksi STEEL! ASSUME A FIXED BASE ANDA PINGED TOP (CASE C) WIDE FLANGE SHAPES HP Axis Y-Y Theoretical Dimensions and Properties for Designing Flange Axis X-X | Weight Area Depth Web Section per of of Thick- Thick- Number Foot Section Section Width S 'T Sy Ty ness ness < * A by tw in. in. in.' in. in....
The subjects in the data are college students. In the data, id is student ID, anxiety is student’s anxiety score via Anxiety Scale, selfest is student’s self-esteem score via Rosenberg Self-esteem Scale, GPA is student’s GPA; for gender, 0=female, 1=male; for grade, 1=freshman, 2=junior, 3=senior. We have known that population mean for Anxiety Scale is μ=60 with σ=10. Raise relevant questions ( 2 questions is fine) about the data extensively, the questions can be either about descriptive analysis or inferential...