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Concrete Mixture Strengths 136
An engineer measures the strength in pounds per square inch (psi) of concrete for 3 different mixtures of concrete. He randomly selects 9 samples from each of the three different mixtures and records their breaking strengths in psi. Assume the samples are independent of each other.  kfoong  Dec 10, 2019  223B  36 
US Presidential Data
This data set gives information on the US Presidents from 17892019. The following data is included:
College,
Religion,
Number of Children,
Age at Inauguration,
Year of Inauguration,
Date at Death,
Political Party,
and Occupation
This data set was originally uploaded to StatCrunch via the khoffman2014 user.  statcrunch_featured  Nov 13, 2019  3KB  361 
SLR: alligator dimensions
p. 518 in Richard L Scheaffer, James T. McClave
Probability and Statistics for Engineers (4th ed.)
Belmont, California: Duxbury Press (1995)
Found originally in the Australian site.
Originally from the Florida Game and Freshwater Fish Commission but I can't find their source.
Length in inches?
Weight in lbs.?  phil_larson  Sep 13, 2012  174B  1140 
NSF 2008 Salary and Gender
Data obtained from the National Science Foundation, National Center for Science and Engineering Statistics (NCSES) 2008 Survey of Doctoral Recipients.  wenorton  Feb 9, 2017  8KB  707  Body Dimensions
NAME: Exploring Relationships in Body Dimensions
TYPE: Observational
SIZE: 507 Observations, 25 Variables
DESCRIPTIVE ABSTRACT:
This dataset contains 21 body dimension measurements as well as age,
weight, height, and gender on 507 individuals. The 247 men and 260
women were primarily individuals in their twenties and thirties, with a
scattering of older men and women, all exercising several hours a week.
SOURCE:
Measurements were initially taken by the first two authors  Grete
Heinz and Louis J. Peterson  at San Jose State University and at the
U.S. Naval Postgraduate School in Monterey, California. Later,
measurements were taken at dozens of California health and fitness
clubs by technicians under the supervision of one of these authors.
VARIABLE DESCRIPTIONS:
Columns Variable
Skeletal Measurements:
1  4 Biacromial diameter (see Fig. 2)
6  9 Biiliac diameter, or "pelvic breadth" (see Fig. 2)
11  14 Bitrochanteric diameter (see Fig. 2)
16  19 Chest depth between spine and sternum at nipple level,
midexpiration
21  24 Chest diameter at nipple level, midexpiration
26  29 Elbow diameter, sum of two elbows
31  34 Wrist diameter, sum of two wrists
36  39 Knee diameter, sum of two knees
41  44 Ankle diameter, sum of two ankles
Girth Measurements:
46  50 Shoulder girth over deltoid muscles
52  56 Chest girth, nipple line in males and just above breast
tissue in females, midexpiration
58  62 Waist girth, narrowest part of torso below the rib cage,
average of contracted and relaxed position
64  68 Navel (or "Abdominal") girth at umbilicus and iliac crest,
iliac crest as a landmark
70  74 Hip girth at level of bitrochanteric diameter
76  79 Thigh girth below gluteal fold, average of right and left
girths
81  84 Bicep girth, flexed, average of right and left girths
86  89 Forearm girth, extended, palm up, average of right and
left girths
91  94 Knee girth over patella, slightly flexed position, average
of right and left girths
96  99 Calf maximum girth, average of right and left girths
101 104 Ankle minimum girth, average of right and left girths
106 109 Wrist minimum girth, average of right and left girths
Other Measurements:
111114 Age (years)
116120 Weight (kg)
122126 Height (cm)
128 Gender (1  male, 0  female)
The first 21 variables are all measured in centimeters (cm).
Values are separated by blanks. There are no missing values.
STORY BEHIND THE DATA:
The first two authors investigated the correspondence between frame
size, girths, and weight of physically active young men and women, most
of whom were within normal weight range. One goal of this investigation
was to develop predictive techniques to assess the lean/fat body
composition of individuals.
PEDAGOGICAL NOTES:
These data can be used to provide statistics students practice in the art
of data analysis. Such analyses range from simple descriptive displays
to more complicated multivariate analyses such as multiple regression
and discriminant analysis.
SUBMITTED BY:
Grete Heinz
24710 Upper Trail
Carmel, CA 93923
USA
goguh@aol.com
Louis J. Peterson
Department of Health Sciences
San José State University
One Washington Square
San José, California 95192
USA
Roger W. Johnson
Department of Mathematics and Computer Science
South Dakota School of Mines and Technology
501 East St. Joseph Street
Rapid City, South Dakota 57701
USA
Roger.Johnson@sdsmt.edu
Carter J. Kerk
Industrial Engineering Program
South Dakota School of Mines and Technology
501 East St. Joseph Street
Rapid City, South Dakota 57701
USA
Carter.Kerk@sdsmt.edu

 hancocd  Mar 19, 2017  8KB  1032  NSF 2008 Salary and Gender
Data obtained from the National Science Foundation, National Center for Science and Engineering Statistics (NCSES) 2008 Survey of Doctoral Recipients.  jmanthey  Aug 31, 2013  8KB  628  QC1
Each hour, a sample of four bearings is chosen from a
manufacturing process. The observation is (x  0.9750)/0.0001,
where x is the diameter of the bearing in inches.
Reference: Johnson, R. A. (1994) Miller and Freund's Probability and
Statistics for Engineers, Fifth Edition. Prentice Hall: Englewood
Cliffs, New Jersey.
Column  Description 
obs1  first observation 
obs2  second observation 
obs3  third observation 
obs4  fourth observation 
 sampleuser  May 25, 2007  323B  349  humidifiers
Humidifier moisture output, oz/hr, used in Statistics.com's introductory statistics course. Drawn from example in T. Ryan's Modern Engineering Statistics (Wiley Interscience, Hoboken, 2007), which was, in turn, drawn from a study by Nelson in the Journal of Quality Technology (v. 21, No. 4, pp. 232241, 1989)  petercbruce  Nov 28, 2012  83B  94  STAT 509 class data
Real data collected from students taking STAT 509 (Statistics for Engineers and Scientists) at the University of South Carolina. A * indicates a missing (unavailable) observation.
Column  Description 
shoe  shoe size 
gender  (0 = Male, 1 = Female) 
state  (0 = out of state, 1= in state) 
field 
1 = computer science / information systems
2 = math
3 = engineering
4 = other

major  USC code for major 
heart  heartbeat (per minute) 
 sampleuser  May 25, 2007  580B  191  QC2
Each day, a sample of 100 units is selected, with the number of defective recorded for each sample. Reference: Johnson, R. A. (1994) Miller and Freund's Probability and
Statistics for Engineers, Fifth Edition. Prentice Hall: Englewood
Cliffs, New Jersey.
Column  Description 
defects  number of defective recorded for each sample 
 sampleuser  May 25, 2007  98B  152  STAT 509 class data
Real data collected from students taking STAT 509 (Statistics for Engineers and Scientists) at the University of South Carolina. A * indicates a missing (unavailable) observation.
Column  Description 
shoe  shoe size 
gender  (0 = Male, 1 = Female) 
state  (0 = out of state, 1= in state) 
field 
1 = computer science / information systems
2 = math
3 = engineering
4 = other

major  USC code for major 
heart  heartbeat (per minute) 
 mystatcourse  Aug 10, 2008  664B  96  QC1
Each hour, a sample of four bearings is chosen from a
manufacturing process. The observation is (x  0.9750)/0.0001,
where x is the diameter of the bearing in inches.
Reference: Johnson, R. A. (1994) Miller and Freund's Probability and
Statistics for Engineers, Fifth Edition. Prentice Hall: Englewood
Cliffs, New Jersey.
Column  Description 
obs1  first observation 
obs2  second observation 
obs3  third observation 
obs4  fourth observation 
 mystatcourse  Aug 10, 2008  374B  51  AYK 3.6 Speed Limit
Based on T. N. Lam, "Estimating fuel consumption from engine size," Journal of Transportation Engineering, 111 (1985), pp. 339357. The data for 10 to 50 km/h are measured; those for 60 km/h and higher are calculated from a model given in the paper and are therefore smoothed.  bbeard  Aug 11, 2008  205B  44  QC2
Each day, a sample of 100 units is selected, with the number of defective recorded for each sample. Reference: Johnson, R. A. (1994) Miller and Freund's Probability and
Statistics for Engineers, Fifth Edition. Prentice Hall: Englewood
Cliffs, New Jersey.
Column  Description 
defects  number of defective recorded for each sample 
 mystatcourse  Aug 10, 2008  141B  37 
Filling Machines  statcrunch  Feb 26, 2009  194B  48 
