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Showing 1 to 15 of 619 data sets matching FINAL
Data Set/Description Owner Last edited Size Views
Edward Lipchus MA181 final exam data. Data are gasoline receipts for my 2006 Ford Focus SXW.
trilsysDec 5, 20192KB53
PRRS Vaccine Final
A researcher was testing the effectiveness of vaccines on the swine disease called PRRS. The researcher randomly split a group of 650 swine into 13 groups of 50 swine. Each group was randomly assigned to one of 4 treatment groups. Each treatment group was given the specific treatment and was then injected with the PRRS virus. The results show the number of swine that test positive for PRRS 30 days after infection.
mariebuseDec 2, 2019127B36
FIFA World Cup Match Results (1930-2014)
This data set records all World Cup Men's soccer matches played between 1930 and 2014. Included is the date of the match, the location, the World Cup Stage (Stage), both teams, the halftime score, the final score, and the attendance for the game.
statcrunch_featuredAug 1, 2018102KB2912
Times World University Rankings (2011-2016)
This data comes from the annual Times magazine rankings of universities across the world. The webpage for the Times 2016 rankings is listed above in the source.
The formula for the 2016 rankings is as follows:
30% for Teaching Rating
7.5% for International Outlook Rating
30% for Research Rating
30% for Citations Rating
2.5% for Industry Income Rating.
The “Total Score” from 2016 can be recreated using this formula.

World_RankUniversity rank for a given year
University_NameThe name of the university
CountryLocation of university
Teaching_Rating Rating from a 0-100 scale of the quality of teaching at the university. This rating is based on the institution’s reputation for teaching, it’s student/staff ratio, it’s PhD’s/ undergraduate degrees awarded ratio, and it’s institutional income/ academic staff ratio.
Inter_Outlook_Rating Rating from a 0-100 scale of the international makeup of a university. This rating is based the international student percentage, international staff percentage, and the percentage of research papers from the university that include at least one international author.
Research_Rating Rating from a 0-100 scale of quality of research at the university. This rating is based on the university’s reputation, it’s research income/ academic staff ratio, and it’s production of scholarly papers.
Citations_Rating Rating from a 0-100 scale of based on the normalized average of citations by other papers per paper from the university (how often the research from the university is cited by other papers).
Industry_Income_Rating Rating from a 0-100 scale grading how much companies are willing to invest in the universities research. The rating is calculated based on the research income from businesses per academic staff member.
Total_ScoreThe final score used to determine the university ranking based on Teaching_Rating, International_Outlook_Rating, Research_Rating, Citations_Rating, and Industrial_Income_Rating.
Num_StudentsTotal number of students in a given year
Student/Staff_RatioNumber of students per academic staff member
%_Inter_StudentsPercentage of student body who come from a foreign county
%_Female_Students Percentage of student body that is female.
YearAcademic year that the ranking was released. For example, 2016 denotes the 2015-2016 academic year.
statcrunchhelpApr 5, 2016254KB4196
Survey Title: Working Women: Work & Sleep Focus group: Working women. Purpose: To correlate the amount of sleep working women obtain, and level of refreshment) to the amount of hours worked, per week. Data collection method: Social media, in person, telephone, electronic texting, e-mail, and telephonic. Appendix: Contains raw data collected, per contributing person
lorriefrenchMar 28, 20194KB1069
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
Southwest Delays VS Delta Delays
Departure delays taken from southwest airlines data and delta airlines data. Data used for the final T-Test Project for MATH 211.
brookd18Jan 11, 201816KB1211
AP Statistics Predictions 2013-16
GPA = Student's Weighted GPA before beginning AP Statistics PrevMath = The highest math course the student completed at our school prior to AP Stats AP.Ave = The student's average score on the AP exams taken (if available) MathGPA = Unweighted GPA of student's work in math courses MT.MC = Students number correct (out of 40) on the multiple choice section of their midterm (MT) MT.Raw = Student's raw score (out of 100) on the multiple choice and free response sections of a previously released AP exam Locus.Aug = Student's score (out of 100) on the LOCUS diagnostic test in the beginning of the school year S1P = Student's first semester grade as a percentage S1G = Student's first semester letter grade S1F = Student's (scaled) first semester final exam grade (a.k.a. midterm test grade) S2P = Student's second semester grade as a percentage S2G = Student's second semester letter grade Ch 1-4 = Student's raw test average on ch. 1-4 Ch 1-6 = Student's raw test average on ch. 1-6 Ch 1-8 = Students raw test average on ch. 1-8 MT = Student's raw test average on the midterm Ch 1-12=Student's raw test average on ch. 1-12 (entire textbook) Mock 1 = Student's raw score on first mock exam (mid-March) Mock 2 = Student's raw score on second mock exam (late April) Mock 1&2 = Student's average on two mock exams MT&Mock1&2 = Student's average on midterm and two mock exams MT.AP = Student's converted score (1-5) on midterm Mocks.AP = Student's converted score (1-5) on average of two mock exams MT&Mocks.AP = Student's converted score (1-5) on average of MT and two mock exams ACTUAL = student's actual performance on AP exam (blank means student opted out of taking exam) MT.Resid = Actual score - Midterm score Mocks.Resid = Actual score - average Mock exam score MT&Mocks.Resid = Actual score - average midterm and mock exam score
je175Jul 5, 20169KB2321
Final Stats Project
I set out to see if age or gender were factors in the average amount of exercise people participated in per week.
haleymcsweeneyMay 15, 2010195B1434
Attendance Vs. Grade
Compares percent of classes attended with final grade in the class. If you use % missed as the independent variable, you end up with a regression model that allows for interpretation of the intercept and has a negative slope.
lbgreenJan 28, 2019744B1472
Pretest/Exams Sp2011
The first 2 columns are the Pretest Scores for Spring 2011 from the first and third (a retake of a similar version) day of class. The next column is the Exam scores. The final 3 columns show the matched version with scores for everyone who took both the first and second version of the pretest and exam 1.
kkeelingMay 16, 20114KB664
Grades for Principles Economics
These are actual course grades (identifying information has been removed) for principles microeconomics and principles macroeconomics. Exams #1 and #2 are non-cumulative. The midterm (which occurs between exams 1 and 2) is cumulative. The final exam grade is not shown, but the course grade is. Test to see whether there is a significant difference in exam grades in the fall semester versus the spring.
adaviesOct 3, 201019KB636
Group 1 Members - Delaney La Rosa, Thomas Lyons, Ruby Hughes, Maria Millan, Kitra Biebighauser, Shalla Campbell
kitrabFeb 4, 20143KB395
Renewable energy consumption (% of total final energy consumption)
The amount of renewable energy used is expressed as a percentage of the total amount of all energy used. The data was collected from 84 countries divided into two groups: high income and low income. The high income countries: Aruba, Australia, Austria, the Bahamas, Barbados, Belgium,British Virgin Islands, Brunei Darussalam, Canada, Chile, Croatia, Cyprus, Czech Republic, Denmark, Estonia, France, Finland, French Polynesia, Germany, Greece, Hong Kong SR China, Hungary, Iceland, Ireland, Isreal, Italy, Japan, Korea, Latvia, Lithuania, Luxemburg, Macao, Malta, United Kingdom, Uraguay, United Arab Emirates, Malta, Monaca, Netherlands, New Caldonia, New Zealand, Norway, Poland, Portugal, Puerto Rico, Saudi Arabia, Seychelles, Singapore, Slovak Republic, Slovak Republic, Spain, Sweden, Switzerland, Trinidad and Tobago, Turks and Calcos Islands, United Kingdom, United States, Uruguay. The low income countries: Afghanistan, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Comoros, Democratic Republic of the Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Haiti, Korea, Dem. People’s Rep., Liberia, Zimbabwe, Madagascar, Malawi, Mali, Republic of Mozambique, Nepal, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda. The data was collected by OECD/IEA and World Bank to help further research for renewable energy. Spreading the use of renewable energy is important to combat fossil fuels to prevent environmental degradation
ninoprieto4Apr 5, 2017413B428
final survey Sleep group 1-2.xlsx
Final data set for sleep study Statistics class 2015
cawincklerMay 31, 20153KB517

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