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Showing 31 to 45 of 198 data sets matching SPRING
Data Set/Description Share Owner Last edited Size Views
Oil Quality Bank
The Trans-Alaska Pipeline System carries crude oil from Prudhoe Bay on Alaska’s North Slope 800 miles to the port of Valdez, on the southern coast of Alaska. The pipeline carries a mixture of different qualities of oil. Quality of oil is measured in API gravity degrees – the higher the degrees APT, the higher the quality. Because the pipeline mixed oils of different degrees, shippers in Valdez receive oil of different quality than they purchased. To compensate shippers, a “Quality Bank” was established. The owners of the pipeline proposed compensating shippers 15 cents per barrel for every degree below the level to which the shippers agreed. However, a refinery near Fairbanks, which receives 26-degree oil and mixes it with 20-degree oil, objected to the proposal. It suggested a 3.09 – to 5.35-cent differential. Because oil carriers are required to establish “just and reasonable” rates, a hearing before an administrative law judge was held. At the hearing, an expert hired by the shippers produced the accompanying table to show the relationship between quality and price per barrel of Mideast oil.
yescraig_slinkmanMay 3, 2010193B281
Arlington Gasoline Retailers Sampling Frame.xls
This is a sampling frame of all gasoline retailer in Arlington Texas collected in Spring Spemster of 2010. Note that you may need to drag the column lines in order to see the entire data fields.
yescraig_slinkmanApr 8, 201022KB298
Top 25 MLB Pitching, Spring Training 2009, as of 4/3/09yescdcummings12Apr 3, 20092KB191
Top 25 MLB Batting, Spring Training 2009, as of 4/3/09yescdcummings12Apr 3, 20092KB89
Students' heightsyessmcdanie%scJan 17, 200888B291
GPAyessmcdanie%scJan 17, 2008116B667
Number of Siblingsyessmcdanie%scJan 17, 200869B258
Classification2008
This is the breakdown of student classification for Spring 2008.
yessmcdanie%scJan 17, 2008255B184
ClassGenderSpring2008
Here is the male/female breakdown of the Spring 2008 stats class.
yessmcdanie%scJan 17, 2008356B323
MS 132 Spring 2015 Data Project Surveyyesmoyerj@husson.eduApr 25, 20159KB20
Spring15AttitudeStudy.xlsxyestonimarquard@scApr 15, 2015166B19
SPOON - Spring 2015 Stats Class SurveyyeskellyspoonApr 12, 201516KB111
STAT 201 Spring 2015 Lab 9 datayesbbjoanne@hotmail.comApr 9, 2015150B10
Chapter 7 At Home Samples - Spring 2015yeslori.perine@montgomerycollege.eduApr 3, 20151KB21
Low Birth Weight Study
OURCE: Hosmer and Lemeshow (2000) Applied Logistic Regression: Second Edition Data were collected at Baystate Medical Center, Springfield, Massachusetts during 1986. DESCRIPTIVE ABSTRACT: The goal of this study was to identify risk factors associated with giving birth to a low birth weight baby (weighing less than 2500 grams). Data were collected on 189 women, 59 of which had low birth weight babies and 130 of which had normal birth weight babies. Four variables which were thought to be of importance were age, weight of the subject at her last menstrual period, race, and the number of physician visits during the first trimester of pregnancy. LIST OF VARIABLES: Columns Variable Abbreviation ----------------------------------------------------------------------------- 2-4 Identification Code ID 10 Low Birth Weight (0 = Birth Weight >= 2500g, LOW 1 = Birth Weight < 2500g) 17-18 Age of the Mother in Years AGE 23-25 Weight in Pounds at the Last Menstrual Period LWT 32 Race (1 = White, 2 = Black, 3 = Other) RACE 40 Smoking Status During Pregnancy (1 = Yes, 0 = No) SMOKE 48 History of Premature Labor (0 = None 1 = One, etc.) PTL 55 History of Hypertension (1 = Yes, 0 = No) HT 61 Presence of Uterine Irritability (1 = Yes, 0 = No) UI 67 Number of Physician Visits During the First Trimester FTV (0 = None, 1 = One, 2 = Two, etc.) 73-76 Birth Weight in Grams BWT ----------------------------------------------------------------------------- PEDAGOGICAL NOTES: These data have been used as an example of fitting a multiple logistic regression model. STORY BEHIND THE DATA: Low birth weight is an outcome that has been of concern to physicians for years. This is due to the fact that infant mortality rates and birth defect rates are very high for low birth weight babies. A woman's behavior during pregnancy (including diet, smoking habits, and receiving prenatal care) can greatly alter the chances of carrying the baby to term and, consequently, of delivering a baby of normal birth weight. The variables identified in the code sheet given in the table have been shown to be associated with low birth weight in the obstetrical literature. The goal of the current study was to ascertain if these variables were important in the population being served by the medical center where the data were collected. References: 1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989).
yeslauren.bartschMar 24, 20156KB67

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