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Showing 1 to 15 of 17 data sets matching engineer
Data Set/Description Owner Last edited Size Views
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.
kfoongDec 10, 2019223B36
US Presidential Data
This data set gives information on the US Presidents from 1789-2019. 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_featuredNov 13, 20193KB361
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_larsonSep 13, 2012174B1140
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.
wenortonFeb 9, 20178KB707
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, mid-expiration 21 - 24 Chest diameter at nipple level, mid-expiration 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, mid-expiration 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: 111-114 Age (years) 116-120 Weight (kg) 122-126 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 --
hancocdMar 19, 20178KB1032
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.
jmantheyAug 31, 20138KB628
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.
ColumnDescription
obs1first observation
obs2second observation
obs3third observation
obs4fourth observation
sampleuserMay 25, 2007323B349
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. 232-241, 1989)
petercbruceNov 28, 201283B94
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.
ColumnDescription
shoeshoe 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
majorUSC code for major
heartheartbeat (per minute)
sampleuserMay 25, 2007580B191
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.
ColumnDescription
defectsnumber of defective recorded for each sample
sampleuserMay 25, 200798B152
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.
ColumnDescription
shoeshoe 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
majorUSC code for major
heartheartbeat (per minute)


mystatcourseAug 10, 2008664B96
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.
ColumnDescription
obs1first observation
obs2second observation
obs3third observation
obs4fourth observation
mystatcourseAug 10, 2008374B51
AYK 3.6 Speed Limit
Based on T. N. Lam, "Estimating fuel consumption from engine size," Journal of Transportation Engineering, 111 (1985), pp. 339-357. 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.
bbeardAug 11, 2008205B44
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.
ColumnDescription
defectsnumber of defective recorded for each sample
mystatcourseAug 10, 2008141B37
Filling MachinesstatcrunchFeb 26, 2009194B48

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