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Data Set/Description Owner Last edited Size Views
01. Small Data Sets Intro Stats.xlsx
Small data sets for regression and hypothesis testing
guillermoalvarez21Nov 8, 2019696B48
This data set is the results of the student survey for the Fall 19 semester.
scott.hornSep 11, 2019114KB1187
"coin toss" "Heads or Tails" "Are you Psychic?"
9c9c9a1a-3c74-4b84-b483-2f21091aacc4-102926_d2l_snhumlpOct 27, 20192KB34
Module 3 - Data Set for Descriptive Analysis - FALL 2019.xlsx
PC 702 Module 3 assignment due 10/28/2019
lara.gabriel01Oct 21, 20191KB69
This data set is the results of the student survey for the semesters of Summer 15 to Fall 19.
scott.hornSep 11, 20191MB378
Report on the Loss of the ‘Titanic’ (S.S.) (1990), British Board of Trade Inquiry Report (reprint), Gloucester, UK: Allan Sutton Publishing. Taken from the Journal on Statistical Education Archive, submitted by Dr. Craig Slinkman has recoded the data as self-explanatory nominal variables. yes craig_slinkman Mar 23, 2010 68KB 5
craig_slinkmanMar 23, 201061KB2481
Mother and Daughter Heights.xls
This data set is Galton's Mother and Daughter data set as used in Sanfford Weisberg's Applied Linear Regression, 3rd Edition.
craig_slinkmanApr 10, 201013KB7297
Weekly Gasoline Prices.xlsx
This time series data on the weekly price of regular gasoline in the state of Texas. Data consits of the data decomposed into year-month-day. The prices are givin in cents.
craig_slinkmanMar 25, 201012KB1338
Happiness Data from GSS.xls
These data come from the 2008 General Social Survey. A subset of 190 respondents were selected at random from the full data set. Children = number of children. Education is highest year of education (e.g., 12 = High School; 16 = Bachelors, etc.). Happy: 1 = Not too happy, 2 = Pretty Happy, 3 = Very Happy. Health: 1 = Poor, 2 = Fair, 3 = Good, 4 = Excellent. Income: 1 = Under $1000; 2 = $1000-2999; 3 = $3000-3999; 4 = $4000-4999; 5 = $5000-5999; 6 = $6000-6999; 7 = $7000-7999; 8 = $8000-9999; 9 = $10000-12499; 10 = $12500-14999; 11 = $15000-17499; 12 = $17500-19999; 13 = $20000-22499; 14 = $22500-24999; 15 = $25000-29999; 16 = $30000-34999; 17 = $35000-39999; 18 = $40000-49999; 19 = $50000-59999; 20 = $60000-74999; 21 = $75000-$89999; 22 = $90000-$109999; 23 = $110000-$129999; 24 = $130000-$149999; 25 = $150000+. Married: 0 = No, 1 = Yes. Religious: 1 = Not religious, 2 = Slightly religious, 3 = Moderately religious, 4 = Very religious.
jacobgsimonsApr 20, 20105KB4325
Random Sample of 100 observations from NHANES (which contains more observations). GENDER (1=Male, 2=Female), AGE (years), WEIGHTENG (inches), HEIGHTENG (inches), SIXFOOT (0=No, 1=Yes to being 72 inches or taller), LEGENG (Leg length inches), WAISTENG (Waist circumference inches), THIGHENG (Thigh circumference inches), WAIST28 (0=No, 1=Yes to having waist 28 inches or smaller), HEIGHT65 (0=No, 1=Yes to being 65 inches tall or shorter), BMI30 (0=No, 1=Yes to having Body Mass Index 30 or higher), OVER200 (0=No, 1=Yes to weighing 200 pounds or more).
jph422Sep 16, 20084KB4124
Year of 800 pennies from a local bank, sampled in 2011 (which is why frequency for 2011 is low).
anderson_instructorOct 29, 20184KB1499
Stats from the major league baseball teams for 2013. The last column I added denotes AL for American League and NL for National League. One could possibly conduct a two-sample means test, for example, to find out whether the average runs for the two leagues are equal. Or there are of course lots of regressions one could run.
eykoloNov 4, 20133KB2096
The data in the Old Faithful file gives data about eruptions of the Old Faithful Geyser during October 1980. Variables are Duration in seconds of the current eruption, and Interval, the time to the next eruption. Old Faithful is an important tourist attraction, with up to a thousand people watching it erupt on pleasant summer days. The National Park Service uses data to obtain a prediction of the time to the next eruption.
craig_slinkmanMay 4, 20102KB2557
State Population and Percent Changes 2015.xlsx
This data set is from the Census Bureau. It shows the population in 2010 as compared to estimates in 2015 for every state as well as Puerto Rico. The table also lists the percent change of population of each state as well as the rank of each state as it pertains to the most populous states.
hbarker2Feb 14, 20162KB1433
For what survey produced it, see and inputs of all team mates. Towards the end, some validation was done, deleting data where working hours was less than a work day, or outliers to legally admissible work days. Finally arbitarily long chains which were less likely to be encountered in draws of simulated data (M/F, Degrees etc.. were discarded). A total of 12 observations were thus thrown out. All Credit goes to Team 3,the Instructor, our unnamed Friends in the Nursing profession who enthusiastically did a last minute push through over their extended social media groups for data and the respondents who kindly took out time for the survey. Another thought is about the distribution of hours worked. Wven if random, it "should be" "centered on" certain hours a day* number of days, with deviations from centre penalised, while picking a sample.. The observations 38 appear many times for example, however without an explainable reason (we are talking of work-distribution among nursing staff sample) So do "primes" "47, 37, 29" It is not to argue that they "shouldn't occur", but there has to be some reason for their being so significant/vibrant. At this stage we may conclude that most of the respondents may not have been under full-time nursing employments in strict sense of the term. 42, 48,72,60, 50,40 appearing more often would give us less variation but more regularity in the data. Since we haven't tried stratification, we do not know "how often they should occur". We thus do not re-draw observations.
ugoagwuJun 14, 20142KB1149

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