Mgmt 710 Assignment
This data is published as supplementary material for a peer reviewed paper: https://osf.io/aku2j/
The object of the study to examine the effect of percieved passion of entrepreneurs/pitch/delivery on accepted pitches on funding show called “Dragon’s Den”
The data is randomly selected. 177 samples from a much larger dataset of 864 pitches. Random number selection + curation (not taken seriously)
Each row of data represents a pitch.
We have info on whether the pitch was accepted.
We have info on composition of team
We have some “rating” of passion, and other percieved emotional variables, these are generated by aggregated, independent raters drawn from a pool of 891 participants recruited from Amazon MTurk.
#working directory
setwd("~/Documents/OneDrive - McGill University/R/Classes/MGMT710")
#Packages
library(ggplot2) # plots
library(dplyr) # data manipulation
library(knitr) # to render the HTML renders
#Load datasets
data1<-as_tibble(read.csv("GravitationalPull_Study1and3a.csv",header=T)) #data includes column labels
#exploring the data
#how much data
dim(data1)## [1] 177 33This shows that we have 177 rows (observations) and 33 columns (variables)
#what columns do we have
labels(data1)[[2]]## [1] "ReceivedOffer" "SpeakersPassion" "MainFemale"
## [4] "X..Speakers" "Industry" "Ethnicity"
## [7] "Season" "SociallyResponsible" "X..Females"
## [10] "FF05" "Engineering" "Ethnicity_bin"
## [13] "Industry_bin" "FF05_Bin" "SpeakersPassion.z"
## [16] "SpeakersPassion.low" "SpeakersPassion.high" "X..Speakers.z"
## [19] "X..Speakers.low" "X..Speakers.high" "SinglePresenter"
## [22] "Appropriateness" "Extraversion_s" "Authentic_s"
## [25] "Appropriateness.z" "Appropriateness.low" "Appropriateness.high"
## [28] "Extraversion_s.z" "Extraversion_s.low" "Extraversion_s.high"
## [31] "Authentic_s.z" "Authentic_s.low" "Authentic_s.high"RecievedOffer is the DV in the original study: 1=offer
SpeakersPassion is the “treatment”, hyp being more passion == higher likelihood of getting an offer.
We are interested in what happens to this relationship when slice by gender, industry, etc.
Now, some summary statistics
summary(data1) # univariate statistics## ReceivedOffer SpeakersPassion MainFemale X..Speakers
## Min. :0.0000 Min. :0.25 Min. :0.0000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:1.26 1st Qu.:0.0000 1st Qu.:1.000
## Median :0.0000 Median :1.72 Median :0.0000 Median :1.000
## Mean :0.4068 Mean :1.70 Mean :0.3333 Mean :1.401
## 3rd Qu.:1.0000 3rd Qu.:2.17 3rd Qu.:1.0000 3rd Qu.:2.000
## Max. :1.0000 Max. :3.20 Max. :1.0000 Max. :3.000
##
## Industry Ethnicity Season SociallyResponsible
## Consumer NonDurables:103 Min. :1.000 Min. :1.000 Min. :0.00000
## Other : 23 1st Qu.:1.000 1st Qu.:4.000 1st Qu.:0.00000
## Consumer Durables : 15 Median :1.000 Median :5.000 Median :0.00000
## Shops : 14 Mean :1.203 Mean :5.028 Mean :0.08475
## Hi-Tech : 9 3rd Qu.:1.000 3rd Qu.:7.000 3rd Qu.:0.00000
## Health : 4 Max. :6.000 Max. :8.000 Max. :1.00000
## (Other) : 9
## X..Females FF05 Engineering Ethnicity_bin
## Min. :0.0000 Min. :1.000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:1.000 1st Qu.:0.0000 1st Qu.:0.0000
## Median :0.0000 Median :1.000 Median :0.0000 Median :0.0000
## Mean :0.4689 Mean :1.763 Mean :0.1751 Mean :0.0904
## 3rd Qu.:1.0000 3rd Qu.:2.000 3rd Qu.:0.0000 3rd Qu.:0.0000
## Max. :2.0000 Max. :5.000 Max. :1.0000 Max. :1.0000
##
## Industry_bin FF05_Bin SpeakersPassion.z SpeakersPassion.low
## Min. :0.0000 Min. :0.0000 Min. :-2.41025 Min. :-1.4102
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:-0.73191 1st Qu.: 0.2681
## Median :1.0000 Median :1.0000 Median : 0.03248 Median : 1.0325
## Mean :0.5819 Mean :0.7458 Mean : 0.00000 Mean : 1.0000
## 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.: 0.78026 3rd Qu.: 1.7803
## Max. :1.0000 Max. :1.0000 Max. : 2.49183 Max. : 3.4918
##
## SpeakersPassion.high X..Speakers.z X..Speakers.low X..Speakers.high
## Min. :-3.4102 Min. :-0.7207 Min. :0.2793 Min. :-1.721
## 1st Qu.:-1.7319 1st Qu.:-0.7207 1st Qu.:0.2793 1st Qu.:-1.721
## Median :-0.9675 Median :-0.7207 Median :0.2793 Median :-1.721
## Mean :-1.0000 Mean : 0.0000 Mean :1.0000 Mean :-1.000
## 3rd Qu.:-0.2197 3rd Qu.: 1.0760 3rd Qu.:2.0760 3rd Qu.: 0.076
## Max. : 1.4918 Max. : 2.8727 Max. :3.8727 Max. : 1.873
##
## SinglePresenter Appropriateness Extraversion_s Authentic_s
## Min. :0.0000 Min. :2.667 Min. :2.507 Min. :3.559
## 1st Qu.:0.0000 1st Qu.:4.894 1st Qu.:4.698 1st Qu.:4.747
## Median :1.0000 Median :5.162 Median :5.180 Median :5.113
## Mean :0.6328 Mean :5.135 Mean :5.108 Mean :5.133
## 3rd Qu.:1.0000 3rd Qu.:5.561 3rd Qu.:5.555 3rd Qu.:5.473
## Max. :1.0000 Max. :6.350 Max. :6.571 Max. :6.344
## NA's :1 NA's :1 NA's :1
## Appropriateness.z Appropriateness.low Appropriateness.high
## Min. :-3.941484 Min. :-2.9415 Min. :-4.9415
## 1st Qu.:-0.388286 1st Qu.: 0.6117 1st Qu.:-1.3883
## Median : 0.039600 Median : 1.0396 Median :-0.9604
## Mean :-0.004071 Mean : 0.9959 Mean :-1.0041
## 3rd Qu.: 0.675797 3rd Qu.: 1.6758 3rd Qu.:-0.3242
## Max. : 1.934118 Max. : 2.9341 Max. : 0.9341
## NA's :1 NA's :1 NA's :1
## Extraversion_s.z Extraversion_s.low Extraversion_s.high Authentic_s.z
## Min. :-3.801684 Min. :-2.8017 Min. :-4.8017 Min. :-2.949600
## 1st Qu.:-0.604615 1st Qu.: 0.3954 1st Qu.:-1.6046 1st Qu.:-0.725136
## Median : 0.098837 Median : 1.0988 Median :-0.9012 Median :-0.038727
## Mean :-0.006527 Mean : 0.9935 Mean :-1.0065 Mean :-0.001947
## 3rd Qu.: 0.645309 3rd Qu.: 1.6453 3rd Qu.:-0.3547 3rd Qu.: 0.635732
## Max. : 2.127108 Max. : 3.1271 Max. : 1.1271 Max. : 2.266319
## NA's :1 NA's :1 NA's :1 NA's :1
## Authentic_s.low Authentic_s.high
## Min. :-1.9496 Min. :-3.9496
## 1st Qu.: 0.2749 1st Qu.:-1.7251
## Median : 0.9613 Median :-1.0387
## Mean : 0.9981 Mean :-1.0019
## 3rd Qu.: 1.6357 3rd Qu.:-0.3643
## Max. : 3.2663 Max. : 1.2663
## NA's :1 NA's :140% recieved offers in this data
33% pitches led by women
Mostly white people.
ggplot(data=data1, aes(x=SpeakersPassion)) + #what you want to plot
geom_density(,fill="lightblue")+ # density plot
ggtitle("Distribution of SpeakerPassion")
ggplot(data=data1, aes(x=SpeakersPassion)) +
geom_density(,fill="lightblue")+
facet_wrap(~Industry)+ #slice the data by...
ggtitle("Distribution of SpeakerPassion by industry")
ggplot(data=data1, aes(x=SpeakersPassion)) +
geom_density(,fill="lightblue")+
facet_wrap(~ReceivedOffer)+
ggtitle("Distribution of SpeakerPassion by offer")
ggplot(data=data1, aes(x=SpeakersPassion)) +
geom_density(,fill="lightblue")+
facet_wrap(~MainFemale)+
ggtitle("Distribution of SpeakerPassion for female lead pitcher")
ggplot(data=data1, aes(x=Appropriateness)) +
geom_density(,fill="lightblue")+
facet_wrap(~MainFemale)+
ggtitle("Distribution of percieved appropriateness for female lead pitcher")## Warning: Removed 1 rows containing non-finite values (stat_density).