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Statistical Analysis of Sign-Out Sheets: Exploring Gender and Class Associations

This study examines the relationship between student sign-outs and factors such as gender, class subject, and block time. By analyzing 1481 sign-out sheets, key findings reveal that 61.44% of sign-outs were by females, with patterns showing increased bathroom usage during the later half of the day. Chi-squared tests indicated significant associations between block time, subject choice, and gender. Notable biases and errors in data collection highlight challenges in accurately capturing student behavior. This research contributes valuable insights into student sign-out trends.

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Statistical Analysis of Sign-Out Sheets: Exploring Gender and Class Associations

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Presentation Transcript

  1. Sign Out Sheet Statistics Tim Kariger, Paolo Ramirez, Taylor Young

  2. Description of Topic • Determine if sign outs are associated with: • Gender • Class Subject • Class Block • 1/3 of Block

  3. Procedure • Gather complete sign out sheets from Mr. Rohrmiller • Mrs. McNelis & Mr. Rohrmiller determine gender, and remove name • Recorded Gender, Subject, Time Out, Block and 1/3 of Block

  4. Gender proportions • Of the 1481 subjects, 61.44% were female 38.56% were male

  5. Block frequency • 3rd is most frequent, but only by 4 Block 1: 280 (18.9%) Block 2: 349 (23.57%) Block 3: 428 (28.9%) Block 4: 424 (28.63%)

  6. Gender Frequency/Block English Female: unimodal, right skewed Male: bimodal, roughly symmetric Social Studies Female: Unimodal, roughly symmetric Male Unimodal, left skewed

  7. Conclusion about pop. • More females than males used the bathroom • Students use the bathroom more frequently in the later half of the day (3rd & 4th)

  8. Study hall Chi squared test (block vs 3rd) Check: -3rd of block and block number are categories -sign out pages were randomly selected -All counts greater than 5 State: -Categorical data -SRS -All expected counts greater then 5 Conditions met, chi squared distribution, Chi squared test for independence. DF=6 P(x>41.99)= .0001

  9. Study hall Chi squared test (block vs 3rd) cont. • Ho: There is no association between 3rd of block and block given that it’s study hall. • Ha: There is an association between 3rd of block and block given that it’s study hall • We reject the Ho because the p-value of .0001 is less than =.05 • We have sufficient evidence that there is an association between 3rd of block, and block when in study hall

  10. Independence test (block and subject) State: -categorical data -SRS -all expected counts are greater than 5 Check: -Block number and subject are categories -Data randomly collected -All expected cell counts are more than 5 Condition met, chi distribution, Chi squared test for independence P(x>381.2)= .0001 DF=15

  11. Conclusion of block and subject test • Ho: there is no association between subject and block • Ha: there is an association between subject and block • We reject the Ho because the p-value of .0001 is less than alpha=.05 • We have sufficient evidence that there in an association between block and subject

  12. Gender and subject chi squared test Check: -Gender and subject are categories -Data collected randomly -All counts greater than 5 State: -Categorical data -SRS -All expected counts greater than 5 Conditions met, chi squared model Chi squared test for independence Ho: there is no association between gender and subject Ha: there is an association between gender and subject P(x>50)= .0001 DF=5

  13. Gender and subject chi squared test Ho: there is no association between gender and sign out subject Ha: there is an association between gender and sign out subject • We reject the Ho because the p-value of .0001 is less than alpha=.05 • We have sufficient evidence that there is an association between gender and what subject you sign out.

  14. Conclusion • Block of the day helps determine what subject • When in study hall, which 3rd of the block you sign out in has to do with what block of the day you’re in • Which gender you are affects what subject you sign out in.

  15. Bias and errors • Gender was based off name and handwriting • Gender could have been wrongly called • Several names could be either male or female • Monotonous data could have been input wrongly • Teachers have different lunches, sign-outs during lunch could not be counted • Teachers have different plan periods during which they have no students to sign-out

  16. Bias and errors (cont.) • Not all sign-outs were to the bathroom, and we can’t guarantee that all students actually went to the destination they signed • We assume that student accurately signed out at the time specified. • Cannot guarantee that every teacher turns their sheets in

  17. Special Thank You… Santa Claus Osama & ME signing out at THIS time , going to HERE coming back NOW Jesus

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