StatCrunch logo (home)

Data sets shared by StatCrunch members
Showing 1 to 15 of 27 data sets matching liter
Data Set/Description Owner Last edited Size Views
Car Details 2019 Models
This data set contains info on the 2019 models of widely sold cars. MSRP stands for Manufacture Suggested Retail Price, and MPG stands for Miles Per Gallon.

This data set was originally uploaded to StatCrunch by the parasami user.
statcrunch_featuredNov 13, 201921KB646
Alcohol consumption per capita for a number of countries
Alcohol consumption per capita is the estimated amount of pure ethanol, in liters, of total alcohol consumed per adult (15 years and older) in a country during a calendar year. Data include consumption of beer, wine, and spirits. Beer includes barley, maize, millet and sorghum beer. Other beverage categories, such as palm wine, vermouths, cider, and fruit wines may also be included. This data is from 2003.
websterwestJan 8, 200910KB1089
Low Birth Weight Study
SOURCE: 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).
wikipetersonJul 23, 20126KB7983
life.xls
This data gives the literacy rate and life expectancy of 107 countries. Thecdata is somewhat old, source is unknown.
bwachsmuth1Oct 9, 20122KB305
cadmium
https://cdn.coastalscience.noaa.gov/datasets/nsandt/dataFiles/ba/westCoast/SanDiegoBayandRiver_Trace_Elements_Sediment.txt The US EPA has established a Maximum Contaminant Level (MCL) of 0.005 milligrams per liter (mg/L) for cadmium in drinking water.
kaitlynnn29Nov 20, 201940KB9
Hospital Adult Patients
“Age” is given in years. “Educational level” values are defined as follows: 0: no high school degree 2: college graduate 1: high school graduate 3: graduate degree “ Smoking status” values are defined as follows: 0: does not smoke 1: smokes less than one pack per day 2: smokes one or more than one pack per day “Exercise” values are defined as follows: 0: none 2: moderate 1: light 3: heavy “ Weight” is given in pounds. “ Serum cholesterol” is given in milligram percent (mg%). “ Systolic pressure” is given in millimeters of mercury (mm Hg). “ IQ” is given in standard IQ test score values. “Sodium” is given in milliequivalents per liter (mEq/1). “ Gender” is listed as male (M) or female (F). “ Marital status” values are defined as follows: M: married S: single W: widowed D: divorced
shleeSep 4, 20154KB1817
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).
lauren.bartschMar 24, 20156KB986
Low Birth Weight Study
SOURCE: 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).
shleeApr 11, 20166KB781
Hospital Adult Patients Updated
Description: “Age” is given in years. “Educational level” values are defined as follows: no high school degree, college graduate, high school graduate, graduate degree “ Smoking status” values are defined as follows: does not smoke, smokes “Exercise” values are defined as follows: 0: none 2: moderate 1: light 3: heavy “ Weight” is given in pounds. “ Serum cholesterol” is given in milligram percent (mg%). “ Systolic pressure” is given in millimeters of mercury (mm Hg). “ IQ” is given in standard IQ test score values. “Sodium” is given in milliequivalents per liter (mEq/1). “ Gender” is listed as male (M) or female (F). “ Marital status” values are defined as follows: M: married S: single W: widowed D: divorced
cetrohaAug 29, 20176KB662
Heart Disease Deaths and Wine
There is some evidence that drinking moderate amounts of wine helps prevent heart attacks. Here are data on yearly wine consumption (liters of alcohol from drinking wine, per person) and yearly deaths from heart disease (deaths per 100,000 people) in 19 developed nations. (M. H. Criqui, University of California, San Diego, reported in the New York Times, December 28, 1994.) Alcohol Heart disease Alcohol Heart disease Country from wine deaths Country from wine deaths
ds-10519%scAug 11, 2008403B717
Hospital Adult Patients
Description: “Age” is given in years. “Educational level” values are defined as follows: 0: no high school degree 2: college graduate 1: high school graduate 3: graduate degree “ Smoking status” values are defined as follows: 0: does not smoke 1: smokes less than one pack per day 2: smokes one or more than one pack per day “Exercise” values are defined as follows: 0: none 2: moderate 1: light 3: heavy “ Weight” is given in pounds. “ Serum cholesterol” is given in milligram percent (mg%). “ Systolic pressure” is given in millimeters of mercury (mm Hg). “ IQ” is given in standard IQ test score values. “Sodium” is given in milliequivalents per liter (mEq/1). “ Gender” is listed as male (M) or female (F). “ Marital status” values are defined as follows: M: married S: single W: widowed D: divorced
cetrohaJan 22, 20164KB445
Shock Data
NOTE: These data appear and are utilized in "Statistical Analysis: A Computer Oriented Approach" by A.A. Afifi and S.P. Azen. DESCRIPTIVE ABSTRACT: SOURCE: These data were collected at the Shock Research Unit at the University of Southern California, Los Angeles, California. Data on many physiological variables were collected successively in time on each patient. These data represent a special subset of the data that was extracted for the purpose of exercise. Initial measurements (measurements upon admission) and final measurements on the same variables (measurements just before death or discharge) were collected on 113 critically ill patients. CODE-SHEET TABLE: Please note that there are 2 records for each patient. Each record contains 21 fields. Record 1 contains 6 general variables (Id - Shock type) and 14 initial measurements on 14 variables (Systolic pressure - Hematocrit). Record 2 contains the same 6 general variables and 14 final measurements on the 14 variables. Each record also has a record number indicator. Column Variable Units Comment -------------------------------------------------------------------------- 1-4 ID none 5-8 Age yr 9-12 Height cm 13-15 Sex none 1=Male, 2=Female 16 Survival none 1=Survived, 3=Died 17-20 Shock type none 2=Non-shock 3=Hypovolemic shock 4=Cardiogenic shock 5=Bacterial shock 6=Neurogenic shock 7=Other 21-24 Systolic Pressure mm Hg 25-28 Mean arterial pressure mm Hg 29-32 Heart rate beats/min 33-36 Diastolic pressure mm Hg 37-40 Mean central venous Pressure cm H2O 41-44 Body surface index m2 45-48 Cardiac index liters/min m2 49-52 Appearance time sec 53-56 Mean circulation time sec 57-60 Urinary output ml/hr 61-64 Plasma volume index ml/kg 65-68 Red Cell Index ml/kg 69-72 Hemoglobin gm/100 ml 73-76 Hematocrit percent 77-79 Blank 80 Card sequence (Record) none 1=Initial, 2=Final
ds-12%scAug 11, 200818KB455
Wolf River Pollution
Jaffe, Parker and Wilson (1982) have investigated the concentration of several hydrophobic organic substances (such as hexachlorobenzene, chlordane, heptachlor, aldrin, dieldrin, endrin) in the Wolf River in Tennessee. Measurements were taken downstream of an abandoned dump site that had previously been used by the pesticide industry to dispose of its waste products. It was expected that these hydrophic substances might have a nonhomogeneous vertical distribution in the river because of differences in density between these compounds and water and because of the adsorption of these compounds on sediments, which could lead to higher concentrations on the bottom. It is important to check this hypothesis because the standard procedure of sampling at six-tenths of the depth could miss the bulk of these pollutants if the distribution were not uniform. Grab samples were taken with a La Motte-Vandorn water sampler of 1 litre capacity at various depths of the river. This sampler consists of a horizontal plexiglas tube of 7 centimetres diameter and a plunger of each side which shuts the sampler when the sampler is at the desired depth. Ten surface, 10 mid-depth and 10 bottom samples were collected, all within a relatively short period. Until they were analysed the samples were stored in 1-quart mason jars at low temperature. In the analysis of the samples, a 250-millilitre water sample was taken from each mason jar and was extracted with 1 millilitre of either hexanes or petroleum ether. A sample of the extract was then injected into a gas chromatograph and the output was compared against standards of known concentrations. The test procedure was repeated two more times, injecting different samples of the extract in the gas chromatograph. The average aldrin and hexachlorobenzene (HCB) concentrations (in nanograms per liter) in these 30 samples are given in the data.
jmantheyApr 17, 2014569B448
Salamander Data.xlsx
Data for 31 Yellow-Spotted Salamanders, from the Kanda Lab at Ithaca College, Central for Natural Sciences, who were sedated with a solution possessing a ratio of 1 liter distilled water/1 gram Oragel (active ingredient 20% benzocaine), until they showed no signs of movement in reaction to a toe-pinch. The salamanders were then rinsed with distilled water, and then a PIT-tag was surgically inserted into the ventral abdominal region, in between the dermis and epidermis tissue layers. Mass and lengths (total length and Snout-Vent Length) were then recorded, and following the salamanders were placed into a Tupperware container surrounded by moist paper towels. At that point, the salamanders were then observed for both 'heads-up' movement and complete recovery (body movement and 'normal behavior'), and the time until these took place was recorded. The variables include Gender, Total Length (cm), Snout-Vent Length [The measurement is from the tip of the nose (snout) to the anus (vent), and excludes the tail] (cm), Mass (g), and Recovery Time (minutes).
matthewqbrooksApr 30, 2013854B206
illiteracy ratebeaucorkinsSep 24, 2014317B820

1 2   >

Always Learning