
Data sets shared by StatCrunch members
Showing 1 to 15 of 122 data sets matching GPA
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Graduate Admissions
The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 )  brmorgante  Jan 15, 2019  12KB  370 
Class Seating vs Grade
From Body Image Data Set:
"A student survey was conducted at a major university. Data were collected from a random sample of 239 undergraduate students".
Variables:
Gender  Male or Female,
GPA  Student's cumulative college GPA.
GPA is then converted to Grades
(where,
4.33 = A+,
4.00 = A,
3.67 = A,
3.33 = B+,
3.00 = B,
2.67 = B,
2.33 = C+,
2.00 = C,
1.67 = C).
Seat  Typical classroom seat location (Front & Back)  mallirhea86  Oct 26, 2018  2KB  2633 
AP Statistics Predictions 201316
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 14 = Student's raw test average on ch. 14
Ch 16 = Student's raw test average on ch. 16
Ch 18 = Students raw test average on ch. 18
MT = Student's raw test average on the midterm
Ch 112=Student's raw test average on ch. 112 (entire textbook)
Mock 1 = Student's raw score on first mock exam (midMarch)
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 (15) on midterm
Mocks.AP = Student's converted score (15) on average of two mock exams
MT&Mocks.AP = Student's converted score (15) 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
 je175  Jul 5, 2016  9KB  1994 
Seating Choice versus GPA (For 3 rows, with Text and Indicator Columns)
This dataset contains hypothetical (I believe) data on GPA for students who sit in the front, middle, and back rows of a classroom, as well as a hypothetical gender variable. The data are shown using both text variables (e.g., "front" and "middle") and 0/1 indicator variables for the row and gender variables. This dataset is useful for demonstrating the different ways that StatCrunch can compare means based on two factors: (a) the text factor columns can be used in a twoway ANOVA; and (b) the 0/1 indicator columns can be used in multiple regression. (Because of StatCrunch's current limitation on equal cells, the 0/1 variables only use the first and middle rows.) Both procedures gives the same pvalue and same conclusion (as long as the interaction term is centered), thus highlighting the similarity of statistical procedures and StatCrunch's flexibility.  bartonpoulson  Apr 7, 2010  1KB  5290 
Seating Choice versus GPA (Stacked & Split Columns for Front & Back Rows)
This dataset contains hypothetical (I believe) data on GPA for students who sit in the front and back row of a classroom. The data are shown in several ways: (a) two separate columns (one for the front row GPA and another or the back row GPA); (b) stacked with one column to indicate front or back row and another column with the GPAs; and (c) the row column repeated as a 0/1 indicator variable.
This dataset is useful for comparing the different ways that StatCrunch can compare the means of two groups: (a) The two columns of scores (front and back) can be used in the 2sample ttest or a oneway ANOVA; (b) the stacked text column (front/back) with a separate column for GPA can also be used for oneway ANOVA; and (c) the 0/1 indicator column and stacked GPAs can be used with correlation and regression. Every procedure gives the same pvalue and same conclusion, thus highlighting the similarity of statistical procedures and StatCrunch's flexibility.  bartonpoulson  Apr 7, 2010  465B  2548 
Body Image Data Set
A student survey was conducted at a major university. Data were collected from a random sample of 239 undergraduate students, and the information that was collected included physical characteristics (such as height, handedness, etc.), study habits, academic performance and attitudes, and social behaviors. In this exercise, we will focus on exploring relationships between some of those variables. Note that empty boxes signify that this observation is not available (this is known as a 'missing value').Variables:
Variables
Gender  Male or Female
Height  Selfreported height (in inches)
GPA  Student's cumulative college GPA
HS_GPA  Student's high school GPA (senior year)
Seat  Typical classroom seat location (F = Front, M = Middle, B = Back)
WtFeel  Does the student feel that he/she is: Underweight, About Right, Overweight
Cheat  Would the tell the instructor if he/she saw somebody cheating on exam? (No or Yes)
 stjohn314  Apr 8, 2018  10KB  2451 
Body Image Data Set
A student survey was conducted at a major university. Data were collected from a random sample of 239 undergraduate students, and the information that was collected included physical characteristics (such as height, handedness, etc.), study habits, academic performance and attitudes, and social behaviors. In this exercise, we will focus on exploring relationships between some of those variables. Note that empty boxes signify that this observation is not available (this is known as a 'missing value').Variables:
Variables
Gender  Male or Female
Height  Selfreported height (in inches)
GPA  Student's cumulative college GPA
HS_GPA  Student's high school GPA (senior year)
Seat  Typical classroom seat location (F = Front, M = Middle, B = Back)
WtFeel  Does the student feel that he/she is: Underweight, About Right, Overweight
Cheat  Would the tell the instructor if he/she saw somebody cheating on exam? (No or Yes)
 33225049_ecollege_sacmlp  Jul 1, 2015  7KB  7430 
Intro Stats GPA
Grade point average for 24 students in intro stats class.
Create a histogram for GPA (If not using StatCrunch, you may want to create a frequency distribution first.) Note: May need to try different bin widths (e.g. 0.5, 1). Is the data continuous or discrete? Comment on the shape of the distribution.  smcdaniel04  Jan 23, 2012  178B  1647 
TibbyCatt COC Students GPA Seating in Class 4 Row 2017 Fall
Randomly selected student data. Random Drawing plus last digit of year on drawn coin for systematic random sample data. Use 4 row, 3 row and 2 row entries with digits.  clstine  Nov 10, 2017  2KB  167 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  7 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  1 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  1 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  0 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  0 
GPA.xlsx  eingram4  Feb 20, 2019  14KB  0 

