
Data sets shared by StatCrunch members
Showing 1 to 15 of 32 data sets matching CLASSROOM
Data Set/Description 
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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  3779 
Years of Classroom Teaching Experience
These data represent the years of experience of prekindergarten through 8th grade teachers attending a summer professional development workshop, 2013
Suggested uses:
 Make a histogram or pie chart.
 Make a stemplot.
 Compute the measures of central tendency and the fivenumber summary.  stephen  Aug 27, 2013  267B  930 
AMSTAT Census at School
This is a random sample (n=250) from the AMSTAT Census at School classroom project.  squesen  Jul 14, 2015  20KB  1483 
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  5640 
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  2707 
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  3192 
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  7697 
Improving Reading Ability
Results of an experiment to test whether directed reading activities in the classroom help elementary school students improve aspects of their reading ability. A treatment class of 21 thirdgrade students participated in these activities for eight weeks, and a control class of 23 thirdgraders followed the same curriculum without the activities. After the eightweek period, students in both classes took a Degree of Reading Power (DRP) test which measures the aspects of reading ability that the treatment is designed to improve. Number of cases: 44 Reference: Moore, David S., and George P. McCabe (1989). Introduction to the Practice of Statistics [Two sample ttest , Summary statistics]
Variable  Description  Treatment  Whether student participated in activities (treated) or not (control)  Response  Score on Degree of Reading Power test 
 statcrunchhelp  Sep 4, 2014  527B  1274 
Cereal Brands  S. Lohse
This data was posted as a shared data set on StatCrunch by owner ntorno8. I am using it as a classroom example in my statistics classes.
Data on several variable of different brands of cereal. Number of cases: 77 Variable Names: Name: Name of cereal mfr: Manufacturer of cereal where A = American Home Food Products; G = General Mills; K = Kelloggs; N = Nabisco; P = Post; Q = Quaker Oats; R = Ralston Purina type: cold or hot calories: calories per serving protein: grams of protein fat: grams of fat sodium: milligrams of sodium fiber: grams of dietary fiber carbo: grams of complex carbohydrates sugars: grams of sugars potass: milligrams of potassium vitamins: vitamins and minerals  0, 25, or 100, indicating the typical percentage of FDA recommended shelf: display shelf (1, 2, or 3, counting from the floor) weight: weight in ounces of one serving cups: number of cups in one serving rating: a rating of the cereals  slohse9395  May 17, 2017  4KB  949 
The Unofficial 2014 NFL Player Census  S. Lohse
This data set is a shared data set owned by websterwest and last updated May 2015. It is being used for examples in my classroom.
Original Description: This data set contains a number of variables on every NFL player participating in the 2014 season. Most of the variables should be self explanatory. Salary represents the average annual salary for the player under their existing contract. Exp represents years of experience. Pro Bowler represents the number of years the player was selected for the pro bowl. Champ provides the number of championship teams on which the player has played. Heisman represents whether or not the player won the Heisman trophy in college.  slohse9395  Feb 11, 2019  321KB  472 
Maria's Data Analysis
Maria's Classroom data to be used for the Sampling Variability Project  ninibb1  Jun 14, 2016  2KB  360 
edit#gid=0
As part of the Math Leadership Corp (MLC) collaborative process, Teachers continually use student formative and summative data to improve their instructional practice and influence their colleagues through research informed coaching, coplanning, classroom observations, demonstrations and critical reflection of practice. Being part of the MLC program, Ms. Garcia’s has researched the role that questioning plays in the classroom from a students’ perspective. Using research she read from Make One Change, teach students to ask questions, she has decided to teach “students, rather than teachers, assume responsibility for posing questions”. She will gather categorical data to see if 80% of 8th grade students feel that asking questions in a math classroom is helpful and whether their is a relationship between asking questions and higher performance on math assessments.
The first and second column:
I found that posing and asking questions is helpful
Helpful (1)
just another thing to do (2)
not helpful (0)
I found that taking notes after discussing the questions with my peers was...
Helpful (1)
just another thing to do (2)
not helpful (0)
Third column are Interim scores
Fourth column Interim scale
Fifth column students who asked questions on Interim
Sixth column students grades on in class assessment
Seventh column  students who asked questions on class assessment  ninibb1  Jun 21, 2016  62KB  299  Yellow/Green exam data
Students were randomly assigned to a version of an exam (Yellow or Green) when they entered the classroom. Afterwards, both sets of students complained about the exam saying their version was harder. Using a randomization approach, determine if the observed data shown above verifies this claim.  websterwest  Mar 11, 2010  201B  502  Seating Choice vs GPA
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.  esther.boyd  Mar 11, 2019  210B  126  Improving Reading Ability
Results of an experiment to test whether directed reading activities in the classroom help elementary school students improve aspects of their reading ability. A treatment class of 21 thirdgrade students participated in these activities for eight weeks, and a control class of 23 thirdgraders followed the same curriculum without the activities. After the eightweek period, students in both classes took a Degree of Reading Power (DRP) test which measures the aspects of reading ability that the treatment is designed to improve.
Number of cases: 44
Reference: Moore, David S., and George P. McCabe (1989). Introduction to the Practice of Statistics[Two sample ttest , Summary statistics]
Variable  Description 
Treatment  Whether student participated in activities (treated) or not (control) 
Response  Score on Degree of Reading Power test 
 ds231%sc  Aug 11, 2008  571B  415 

