gateway_data = read.csv(file = "gateway survey.csv")
head(gateway_data)
projects = gateway_data$projects
knowledge = gateway_data$understanding
train = gateway_data$train
recommend = gateway_data$recommend
backlog_management = gateway_data$backlog.manage
sl_user_exp = gateway_data$sl.exp
customer_experience = gateway_data$customer.exp
story_refinement = gateway_data$refinement
client_story_acception = gateway_data$client.accept
client_todo = gateway_data$to.do
release_planning = gateway_data$release
sprint_planning = gateway_data$sprint.plan
sprint_management = gateway_data$sprint.manage
story_editing = gateway_data$story.edit
summary(gateway_data)
     Order    
 Min.   : 1   
 1st Qu.: 5   
 Median : 9   
 Mean   : 9   
 3rd Qu.:13   
 Max.   :17   
 NA's   :100  
 How.many.projects.have.you.used.Gateway.on...Including.current.projects.
 Min.   :1.000                                                           
 1st Qu.:1.000                                                           
 Median :1.000                                                           
 Mean   :1.529                                                           
 3rd Qu.:2.000                                                           
 Max.   :5.000                                                           
 NA's   :100                                                             
                                                 What.were.the.projects.you.worked.on.
                                                                    :100              
 Baptist Health                                                     :  2              
 2 Clients (CS has a different sprint structure) Blend & Brand Share:  1              
 AIME                                                               :  1              
 Altium, Comm-Works, FFB, Doctors Only, Project Sunshine            :  1              
 automotive Mastermind                                              :  1              
 (Other)                                                            : 11              
 How.well.do.you.think.you.understand.how.to.use.the.Gateway.effectively.
 Min.   : 3.000                                                          
 1st Qu.: 7.000                                                          
 Median : 7.000                                                          
 Mean   : 7.176                                                          
 3rd Qu.: 8.000                                                          
 Max.   :10.000                                                          
 NA's   :100                                                             
 How.well.were.you.trained.on.using.the.Gateway.before.you.started.
 Min.   :1.000                                                     
 1st Qu.:2.000                                                     
 Median :3.000                                                     
 Mean   :3.353                                                     
 3rd Qu.:4.000                                                     
 Max.   :7.000                                                     
 NA's   :100                                                       
 How.likely.are.you.to.recommend.the.Gateway.to.be.used.on.your.future.projects.
 Min.   : 1.000                                                                 
 1st Qu.: 5.000                                                                 
 Median : 6.000                                                                 
 Mean   : 6.118                                                                 
 3rd Qu.: 8.000                                                                 
 Max.   :10.000                                                                 
 NA's   :100                                                                    
 Backlog.management.organization Silverline.user.experience Customer.experience
 Min.   :1.000                   Min.   :1.000              Min.   :2.000      
 1st Qu.:5.000                   1st Qu.:3.000              1st Qu.:3.000      
 Median :7.000                   Median :6.000              Median :5.500      
 Mean   :5.824                   Mean   :5.235              Mean   :5.438      
 3rd Qu.:7.000                   3rd Qu.:7.000              3rd Qu.:7.250      
 Max.   :8.000                   Max.   :8.000              Max.   :9.000      
 NA's   :100                     NA's   :100                NA's   :101        
 Story.refinement.with.clients Client.accepting.or.approving.stories
 Min.   :1.000                 Min.   :1.000                        
 1st Qu.:2.750                 1st Qu.:4.750                        
 Median :5.500                 Median :6.500                        
 Mean   :5.375                 Mean   :6.062                        
 3rd Qu.:8.250                 3rd Qu.:8.250                        
 Max.   :9.000                 Max.   :9.000                        
 NA's   :101                   NA's   :101                          
 Managing.client..to.dos..and.tasks Release.planning Sprint.planning
 Min.   :1.000                      Min.   :1.000    Min.   :1.000  
 1st Qu.:2.750                      1st Qu.:2.750    1st Qu.:3.000  
 Median :5.000                      Median :5.000    Median :6.000  
 Mean   :4.562                      Mean   :4.312    Mean   :5.267  
 3rd Qu.:6.250                      3rd Qu.:5.250    3rd Qu.:7.000  
 Max.   :9.000                      Max.   :7.000    Max.   :8.000  
 NA's   :101                        NA's   :101      NA's   :102    
 Sprint.management Drafting.editing.user.stories    X             X.1         
 Min.   :1.000     Min.   : 1.000                Mode:logical   Mode:logical  
 1st Qu.:4.500     1st Qu.: 3.000                NA's:117       NA's:117      
 Median :7.000     Median : 6.000                                             
 Mean   :5.667     Mean   : 5.647                                             
 3rd Qu.:7.500     3rd Qu.: 8.000                                             
 Max.   :8.000     Max.   :10.000                                             
 NA's   :102       NA's   :100                                                
   X.2            X.3            X.4            X.5            X.6         
 Mode:logical   Mode:logical   Mode:logical   Mode:logical   Mode:logical  
 NA's:117       NA's:117       NA's:117       NA's:117       NA's:117

CORRELATIONS BETWEEN PROJECT # AND…

cor(projects,knowledge,use = "complete.obs")
[1] 0.2202582
cor(projects,train,use = "complete.obs")
[1] 0.02786987
cor(projects,recommend,use = "complete.obs")
[1] 0.5166323
cor(projects,backlog_management,use = "complete.obs")
[1] 0.2188239
cor(projects,sl_user_exp,use = "complete.obs")
[1] 0.2302061
cor(projects,customer_experience,use = "complete.obs")
[1] 0.4241866
cor(projects,story_refinement,use = "complete.obs")
[1] 0.431916
cor(projects,client_story_acception,use = "complete.obs")
[1] 0.3592603
cor(projects,client_todo,use = "complete.obs")
[1] -0.3836408
cor(projects,release_planning,use = "complete.obs")
[1] 0.2239232
cor(projects,sprint_planning,use = "complete.obs")
[1] 0.3695943
cor(projects,sprint_management,use = "complete.obs")
[1] 0.3394514
cor(projects,story_editing,use = "complete.obs")
[1] 0.2059582

CORRELATIONS BETWEEN KNOWLEDGE AND…

cor(knowledge,projects,use = "complete.obs")
[1] 0.2202582
cor(knowledge,train,use = "complete.obs")
[1] 0.6983325
cor(knowledge,recommend,use = "complete.obs")
[1] 0.3466897
cor(knowledge,backlog_management,use = "complete.obs")
[1] 0.3915122
cor(knowledge,sl_user_exp,use = "complete.obs")
[1] 0.4420609
cor(knowledge,customer_experience,use = "complete.obs")
[1] 0.06624267
cor(knowledge,story_refinement,use = "complete.obs")
[1] 0.1987571
cor(knowledge,client_story_acception,use = "complete.obs")
[1] -0.004784829
cor(knowledge,client_todo,use = "complete.obs")
[1] 0.08693006
cor(knowledge,release_planning,use = "complete.obs")
[1] 0.1729495
cor(knowledge,sprint_planning,use = "complete.obs")
[1] 0.4410134
cor(knowledge,sprint_management,use = "complete.obs")
[1] 0.465234
cor(knowledge,story_editing,use = "complete.obs")
[1] 0.4064404
cor(gateway_data)
                     Order    projects understanding       train   recommend
Order           1.00000000  0.17440562   -0.22152269 -0.40373128 -0.06585155
projects        0.17440562  1.00000000    0.27907630  0.08250413  0.51257233
understanding  -0.22152269  0.27907630    1.00000000  0.66636902  0.45641501
train          -0.40373128  0.08250413    0.66636902  1.00000000  0.35581369
recommend      -0.06585155  0.51257233    0.45641501  0.35581369  1.00000000
backlog.manage  0.20687552  0.24604070    0.40711497  0.23840966  0.76130827
sl.exp          0.13266460  0.29821604    0.43081191  0.21323513  0.81172493
customer.exp    0.03568066  0.41094491    0.15492533  0.07851603  0.78215495
refinement      0.16319823  0.44426166    0.19448298 -0.03998555  0.77737611
client.accept   0.16799162  0.37762746   -0.05114363 -0.31155823  0.67913348
to.do           0.06412175 -0.36989871    0.02007012  0.02750934  0.45176146
release         0.21426326  0.19221462    0.36066361  0.10061945  0.72938144
sprint.plan    -0.02135822  0.36959433    0.44101335  0.32645508  0.87920381
sprint.manage   0.09099236  0.33945143    0.46523401  0.41362919  0.84273732
story.edit      0.08164968  0.21859806    0.47369005  0.31578687  0.77944692
               backlog.manage    sl.exp customer.exp  refinement client.accept
Order               0.2068755 0.1326646   0.03568066  0.16319823    0.16799162
projects            0.2460407 0.2982160   0.41094491  0.44426166    0.37762746
understanding       0.4071150 0.4308119   0.15492533  0.19448298   -0.05114363
train               0.2384097 0.2132351   0.07851603 -0.03998555   -0.31155823
recommend           0.7613083 0.8117249   0.78215495  0.77737611    0.67913348
backlog.manage      1.0000000 0.7899337   0.66175748  0.72870967    0.61974097
sl.exp              0.7899337 1.0000000   0.70950211  0.73308894    0.66067211
customer.exp        0.6617575 0.7095021   1.00000000  0.96408224    0.70751690
refinement          0.7287097 0.7330889   0.96408224  1.00000000    0.77172084
client.accept       0.6197410 0.6606721   0.70751690  0.77172084    1.00000000
to.do               0.6104070 0.3873788   0.49910606  0.52462739    0.38954104
release             0.9139770 0.7392495   0.72959078  0.80878525    0.68831096
sprint.plan         0.8271048 0.9033632   0.81294191  0.79844616    0.60958799
sprint.manage       0.8981582 0.8565604   0.65436914  0.68365049    0.53147962
story.edit          0.8683172 0.8298330   0.50241557  0.53504723    0.62534480
                     to.do   release sprint.plan sprint.manage story.edit
Order           0.06412175 0.2142633 -0.02135822    0.09099236 0.08164968
projects       -0.36989871 0.1922146  0.36959433    0.33945143 0.21859806
understanding   0.02007012 0.3606636  0.44101335    0.46523401 0.47369005
train           0.02750934 0.1006194  0.32645508    0.41362919 0.31578687
recommend       0.45176146 0.7293814  0.87920381    0.84273732 0.77944692
backlog.manage  0.61040703 0.9139770  0.82710484    0.89815817 0.86831720
sl.exp          0.38737877 0.7392495  0.90336322    0.85656036 0.82983297
customer.exp    0.49910606 0.7295908  0.81294191    0.65436914 0.50241557
refinement      0.52462739 0.8087852  0.79844616    0.68365049 0.53504723
client.accept   0.38954104 0.6883110  0.60958799    0.53147962 0.62534480
to.do           1.00000000 0.7252493  0.48757382    0.45889996 0.44247978
release         0.72524934 1.0000000  0.82636704    0.75135616 0.76741842
sprint.plan     0.48757382 0.8263670  1.00000000    0.86591533 0.77528618
sprint.manage   0.45889996 0.7513562  0.86591533    1.00000000 0.79609827
story.edit      0.44247978 0.7674184  0.77528618    0.79609827 1.00000000
str(gateway_data)
'data.frame':   15 obs. of  15 variables:
 $ Order         : int  1 2 4 5 6 7 8 9 10 11 ...
 $ projects      : int  1 1 2 2 1 2 3 1 1 1 ...
 $ understanding : int  9 7 8 7 6 8 8 8 3 9 ...
 $ train         : int  7 1 5 4 2 4 3 4 1 5 ...
 $ recommend     : int  9 2 5 8 9 10 8 7 1 3 ...
 $ backlog.manage: int  7 2 2 8 7 7 8 8 1 4 ...
 $ sl.exp        : int  7 1 2 8 5 7 6 7 1 3 ...
 $ customer.exp  : int  5 3 3 9 8 7 7 8 3 4 ...
 $ refinement    : int  3 2 2 9 9 7 8 9 1 3 ...
 $ client.accept : int  5 4 2 7 9 9 8 8 6 1 ...
 $ to.do         : int  5 2 2 4 9 6 5 7 1 3 ...
 $ release       : int  5 2 2 5 6 5 7 7 1 3 ...
 $ sprint.plan   : int  8 2 3 8 6 6 8 7 1 3 ...
 $ sprint.manage : int  8 1 3 8 7 7 7 8 1 4 ...
 $ story.edit    : int  10 1 2 8 6 9 7 6 1 3 ...
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