SlideShare a Scribd company logo
Data of Ms.Lays Class peroid 2
The data of Ms.Lays 2nd hour




                                                                                                    HandSlap
                     Last Name




                                             First Name




                                                          HeadSize




                                                                      GhostBlaster




                                                                                        StopWatch




                                                                                                               MorF
       1 James                   Dion                                 17             24.31             0m
       2 Matatov                 Sarah                                13             30.09             1f
       3 Nadrozny                Katherine                            -9             30.06             1f
       4 Miller                  Allyson                              17             29.91             1f
       5 Denzer                  Haylie                               28             29.85             1f
       6 Barkan                  Omer                                 29             29.03             1f
       7 Koester                 Sophia                               19             27.11             1f
       8 Nguyen                  Serena                               24             30.25             2f
       9 Yang                    Shirley                              51             30.06             2f
      10 Hall                    Corey                                18             29.99             2m
      11 Sharma                  Abhinav                              33             29.91             2m
      12 Ray                     Megan                               -35             29.84             2f
      13 Ellis                   Sahirah                              28             29.82             2f
      14 Thomas                  George                               41             29.59             2m
      15 Berner                  Riley                                11             30.44             3m
      16 Martin                  Madeline                             17             30.22             3f
      17 Morris                  Elizabeth                            28             29.94             4f
      18 Neitzel                 Alec                                 28             29.83             4m
      19 Donohue                 Drew                                 11             29.62             4m
      20 Fisher                  Ian                                  18             29.03             4m
      21 McNamara                Jonathan                             26             30.12             5m
      22 Miller                  Jackson                              26             29.94             5m
      23 Lemay                   Brian                                32             29.85             5m
      24 Cimarusti               Eric                                 16             30.05             6m
      25 Caughey                 Matthew                              17             29.94             7m
      26 Woods                   Mary                                  2             29.93             7f
      27 Neitzel                 Brady                                36             29.79             7m
Measures of center and range
           GB       SW              HS
Mean       20.07407 29.5704         3.111111
           points   sec             111111
                                    slaps
Median     19 points 29.91 sec 2 slaps
Mode       17 and 28 29.94 sec 2 slaps
           points
Range      86 point 6.13 sec 7 slaps
           neg 35,neg
Outliers   9,2,11, 36,41,
                          24.31 sec No
           and 51 points            outliers
Box plot for Ghost Busters

      Median: 19 Upper Quartile: 28 Lower Quartile: 16
      Minimum: -35 Maximum: 51




-35   -25 -15     -5     5      15     25   35      45   55
Box plot for stop watch

     Median: 29.91 Lower quartile: 29.79 Upper quartile:
     30.05 Minimum: 24.31 Maximum: 30.44




24 24.5 25 25.5 26 26.5 27 27.5 28 28.5 29 29.5 30 30.5 31   31.5
Box Plot for hand slaps
Median: 2 Lower Quartile: 1 Upper Quartile: 4
Minimum: 0 Maximum: 7
                                                        Hand slaps




0      1      2      3     4      5      6      7   8
Bar graph for hand slaps
                   number of hand slaps
                                              I think that the
                                              bar graph best
                                              represents the
7…
                                              data for hand
6…
                                              slaps because it
4…
                                              has a more exact
3…                                            data than the
2…                                            histogram or the
1…                                            line plot.
0…

 0   1     2   3   4      5     6         7
Line plot for ghost blasters
Collection 1




                                                                                                              I think that this best
        10
                                                                                                              represents the
                                                                                                              ghost blasters data
count




                                                                                                              because it shows
        5
                                                                                                              the clusters while
                                                                                                              still separating the
                                                                                                              data to show where
        0                                                                                                     it goes and it also
                                                                                                              shows each person
                                                                                                 100 to 119
                 -40 to -21


                              -20 to -1




                                                     20 to 39


                                                                40 to 59


                                                                           60 to 79


                                                                                      80 to 99
                                          0 to 19




                                                                                                              rather than a bar.

                                                    GhostBlaster
             Circle Icon
Line plot for stop watch
Collection 1




        20                                                                                                            I think that this
                                                                                                                      line plot best
                                                                                                                      shows the data
        15
                                                                                                                      for stop watch
                                                                                                                      times because
count




        10                                                                                                            again it shows
                                                                                                                      each person and it
                                                                                                                      also separates
        5
                                                                                                                      them in groups
                                                                                                                      rather than each
        0                                                                                                             one so the graph
                                                                                                                      would not have to
                 24.3-25.19


                              25.2-26.09


                                           26.1-26.99




                                                                   27.9-28.79


                                                                                28.8-29.69


                                                                                             29.7-30.59


                                                                                                          30.6-31.5
                                                        27-27.89




                                                                                                                      be that big

                                                        StopWatch
             Circle Icon
Variability
• For ghost blasters I think the data clusters around the 16-28
  area. Some gaps though are -35--9, 2-11, 13-16, 11-13, 13-
  16, 19-24, 24-26, 26-28, 29-32, 33-36, 36-41, and 41-51, so that
  shows there was a lot of gaps.
• For hand slaps I think the data clusters around 0-7 area. There is
  no gaps though and it wasn’t spread out.
• For stop watch times I think the cluster is around 29.03-30.44.
  The a tons of gaps in the data, but the data was sort of spread
  out.
Typical sixth grader
• I think that from the data it shows in hand slaps that we are slow
  because the mode of the data is 2 and the median of the data is
  also 2, so that shows they are slow.
• I think also from the data that most people have a good reaction
  times because the median is 29.91 and the mode is 29.94 which
  is really close to 30.00 so it show people can react really fast at
  stop watches.
• I think again from the data that in ghost blasters that they have
  good reactions because it is the data is around 20 (an example is
  than the median is 19 and the mode is 17 and 28)
Who’s Faster boys or girls

The boys are faster
because if you look at the
hand slaps the boys           Collection 1


mean and median are 4
and the girls are 3, and             m


the boys cluster is farther

                              MorF
up than the girls.
                                     f




                                           0    1      2    3   4     5   6   7
                                                           HandSlap
                                         Circle Icon

More Related Content

Similar to Brady Neitzel

Similar to Brady Neitzel (14)

Jonathan Macnamara
Jonathan MacnamaraJonathan Macnamara
Jonathan Macnamara
 
George Thomas
George ThomasGeorge Thomas
George Thomas
 
Alec Neitzel
Alec NeitzelAlec Neitzel
Alec Neitzel
 
Matthew Caughey
Matthew CaugheyMatthew Caughey
Matthew Caughey
 
Haylie Denzer
Haylie DenzerHaylie Denzer
Haylie Denzer
 
Abhi Sharma
Abhi SharmaAbhi Sharma
Abhi Sharma
 
Sahirah Ellis
Sahirah EllisSahirah Ellis
Sahirah Ellis
 
Sahirah Ellis
Sahirah EllisSahirah Ellis
Sahirah Ellis
 
Madeline Martin
Madeline MartinMadeline Martin
Madeline Martin
 
Elizabeth Morris
Elizabeth MorrisElizabeth Morris
Elizabeth Morris
 
Eric Cimarusti
Eric CimarustiEric Cimarusti
Eric Cimarusti
 
Ally Miller
Ally MillerAlly Miller
Ally Miller
 
Corey Hall
Corey HallCorey Hall
Corey Hall
 
Omer Barkan
Omer BarkanOmer Barkan
Omer Barkan
 

Recently uploaded

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
 
ODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupCatarinaPereira64715
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Thierry Lestable
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...Product School
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoTAnalytics
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...Sri Ambati
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
 
Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutesconfluent
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
 
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...Product School
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsExpeed Software
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlPeter Udo Diehl
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform EngineeringJemma Hussein Allen
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Product School
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Alison B. Lowndes
 

Recently uploaded (20)

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
ODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User Group
 
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
 
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
 
"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi"Impact of front-end architecture on development cost", Viktor Turskyi
"Impact of front-end architecture on development cost", Viktor Turskyi
 
Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutes
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT Professionals
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
 
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
 
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualitySoftware Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
 

Brady Neitzel

  • 1. Data of Ms.Lays Class peroid 2
  • 2. The data of Ms.Lays 2nd hour HandSlap Last Name First Name HeadSize GhostBlaster StopWatch MorF 1 James Dion 17 24.31 0m 2 Matatov Sarah 13 30.09 1f 3 Nadrozny Katherine -9 30.06 1f 4 Miller Allyson 17 29.91 1f 5 Denzer Haylie 28 29.85 1f 6 Barkan Omer 29 29.03 1f 7 Koester Sophia 19 27.11 1f 8 Nguyen Serena 24 30.25 2f 9 Yang Shirley 51 30.06 2f 10 Hall Corey 18 29.99 2m 11 Sharma Abhinav 33 29.91 2m 12 Ray Megan -35 29.84 2f 13 Ellis Sahirah 28 29.82 2f 14 Thomas George 41 29.59 2m 15 Berner Riley 11 30.44 3m 16 Martin Madeline 17 30.22 3f 17 Morris Elizabeth 28 29.94 4f 18 Neitzel Alec 28 29.83 4m 19 Donohue Drew 11 29.62 4m 20 Fisher Ian 18 29.03 4m 21 McNamara Jonathan 26 30.12 5m 22 Miller Jackson 26 29.94 5m 23 Lemay Brian 32 29.85 5m 24 Cimarusti Eric 16 30.05 6m 25 Caughey Matthew 17 29.94 7m 26 Woods Mary 2 29.93 7f 27 Neitzel Brady 36 29.79 7m
  • 3. Measures of center and range GB SW HS Mean 20.07407 29.5704 3.111111 points sec 111111 slaps Median 19 points 29.91 sec 2 slaps Mode 17 and 28 29.94 sec 2 slaps points Range 86 point 6.13 sec 7 slaps neg 35,neg Outliers 9,2,11, 36,41, 24.31 sec No and 51 points outliers
  • 4. Box plot for Ghost Busters Median: 19 Upper Quartile: 28 Lower Quartile: 16 Minimum: -35 Maximum: 51 -35 -25 -15 -5 5 15 25 35 45 55
  • 5. Box plot for stop watch Median: 29.91 Lower quartile: 29.79 Upper quartile: 30.05 Minimum: 24.31 Maximum: 30.44 24 24.5 25 25.5 26 26.5 27 27.5 28 28.5 29 29.5 30 30.5 31 31.5
  • 6. Box Plot for hand slaps Median: 2 Lower Quartile: 1 Upper Quartile: 4 Minimum: 0 Maximum: 7 Hand slaps 0 1 2 3 4 5 6 7 8
  • 7. Bar graph for hand slaps number of hand slaps I think that the bar graph best represents the 7… data for hand 6… slaps because it 4… has a more exact 3… data than the 2… histogram or the 1… line plot. 0… 0 1 2 3 4 5 6 7
  • 8. Line plot for ghost blasters Collection 1 I think that this best 10 represents the ghost blasters data count because it shows 5 the clusters while still separating the data to show where 0 it goes and it also shows each person 100 to 119 -40 to -21 -20 to -1 20 to 39 40 to 59 60 to 79 80 to 99 0 to 19 rather than a bar. GhostBlaster Circle Icon
  • 9. Line plot for stop watch Collection 1 20 I think that this line plot best shows the data 15 for stop watch times because count 10 again it shows each person and it also separates 5 them in groups rather than each 0 one so the graph would not have to 24.3-25.19 25.2-26.09 26.1-26.99 27.9-28.79 28.8-29.69 29.7-30.59 30.6-31.5 27-27.89 be that big StopWatch Circle Icon
  • 10. Variability • For ghost blasters I think the data clusters around the 16-28 area. Some gaps though are -35--9, 2-11, 13-16, 11-13, 13- 16, 19-24, 24-26, 26-28, 29-32, 33-36, 36-41, and 41-51, so that shows there was a lot of gaps. • For hand slaps I think the data clusters around 0-7 area. There is no gaps though and it wasn’t spread out. • For stop watch times I think the cluster is around 29.03-30.44. The a tons of gaps in the data, but the data was sort of spread out.
  • 11. Typical sixth grader • I think that from the data it shows in hand slaps that we are slow because the mode of the data is 2 and the median of the data is also 2, so that shows they are slow. • I think also from the data that most people have a good reaction times because the median is 29.91 and the mode is 29.94 which is really close to 30.00 so it show people can react really fast at stop watches. • I think again from the data that in ghost blasters that they have good reactions because it is the data is around 20 (an example is than the median is 19 and the mode is 17 and 28)
  • 12. Who’s Faster boys or girls The boys are faster because if you look at the hand slaps the boys Collection 1 mean and median are 4 and the girls are 3, and m the boys cluster is farther MorF up than the girls. f 0 1 2 3 4 5 6 7 HandSlap Circle Icon