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https://github.com/kidwellj/trs_admissions_survey2021.git
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fixed typos re high in subgroup interest analysis
This commit is contained in:
Jeremy Kidwell
parent
57e574d953
commit
8472d96d3a
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@ -16,6 +16,7 @@ library(RColorBrewer)
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library("stringr") # Load stringr package, used for wrapping label text in plots
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library(dplyr) # Used for filtering below
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library(scales) # Used for adding percentages to bar charts
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library(kable) # Used for generating markdown tables
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# Define colour palettes for plots below
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coul3 <- brewer.pal(3, "RdYlBu") # Using RdYlBu range to generate 3 colour palette: https://colorbrewer2.org/#type=diverging&scheme=RdYlBu&n=5
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@ -234,6 +235,8 @@ Employability_data <- TSR_data[, 30:41]
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```{r Visualization for 4 Key Subjects}
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## Subset by "Positive" / "Negative"
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# jk note: I've filled in the other fields just for fun
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keysubjects_data <- subject_data[subject_data$Subject == "Philosophy" | subject_data$Subject == "Ethics" | subject_data$Subject == "Theology" | subject_data$Subject == "Religious Studies" | subject_data$Subject == "Sociology" | subject_data$Subject == "Psychology" | subject_data$Subject == "History" | subject_data$Subject == "Politics" | subject_data$Subject == "English" | subject_data$Subject == "Math" | subject_data$Subject == "Computer Science" | subject_data$Subject == "Business", ]
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recode_interest <- ifelse(2 <= keysubjects_data$Interest & keysubjects_data$Interest >=4, "Positive", "Negative")
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@ -320,6 +323,13 @@ write.csv(interest_table, "derivedData/interest_table.csv", row.names=TRUE)
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## Mean Interest in Theology and Religious Studies by High/Low Subject Interest
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```{r Philosophy}
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# Base mean:
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mean(as.numeric(TSR_data$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(TSR_data$InterestedinstudyingReligiousStudies), na.rm = TRUE)
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mean(as.numeric(TSR_data$InterestinstudyingPhilosophy), na.rm = TRUE)
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mean(as.numeric(TSR_data$InterestedinStudyingPsychology), na.rm = TRUE)
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### Philosophy ###
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Philos_subset_Low <- TSR_data[TSR_data$InterestinstudyingPhilosophy < 3 & TSR_data$InterestinstudyingPhilosophy != 0, ]
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@ -329,7 +339,7 @@ Philos_subset_High <- TSR_data[TSR_data$InterestinstudyingPhilosophy > 3, ]
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#Low interest in Philosophy
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mean(as.numeric(Philos_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Philosophy
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mean(as.numeric(Philos_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Philos_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Philosophy
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@ -346,9 +356,9 @@ Soc_subset_High <- TSR_data[TSR_data$InterestinstudyingSociaology > 3, ]
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## Theology Interest
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#Low interest in Sociology
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lSocTheo <- mean(as.numeric(Soc_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Soc_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Sociology
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hSocTheo <- mean(as.numeric(Soc_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Soc_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Sociology
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@ -367,7 +377,7 @@ Psych_subset_High <- TSR_data[TSR_data$InterestedinStudyingPsychology > 3, ]
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#Low interest in Psychology
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mean(as.numeric(Psych_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Psychology
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mean(as.numeric(Psych_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Psych_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Psychology
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@ -386,7 +396,7 @@ Hist_subset_High <- TSR_data[TSR_data$InterestedinstudyingHistory > 3, ]
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#Low interest in History
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mean(as.numeric(Hist_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in History
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mean(as.numeric(Hist_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Hist_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in History
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@ -405,7 +415,7 @@ Ethics_subset_High <- TSR_data[TSR_data$InterestedinstudyingEthics > 3, ]
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#Low interest in Ethics
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mean(as.numeric(Ethics_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Ethics
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mean(as.numeric(Ethics_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Ethics_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Ethics
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@ -424,7 +434,7 @@ Polit_subset_High <- TSR_data[TSR_data$InterestedinstudyingPolitics > 3, ]
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#Low interest in Politics
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mean(as.numeric(Polit_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Politics
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mean(as.numeric(Polit_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Polit_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Politics
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@ -443,7 +453,7 @@ Eng_subset_High <- TSR_data[TSR_data$InterestedinstudyingEnglish > 3, ]
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#Low interest in English
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mean(as.numeric(Eng_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in English
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mean(as.numeric(Eng_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Eng_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in English
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@ -454,7 +464,7 @@ mean(as.numeric(Eng_subset_High$InterestedinstudyingReligiousStudies), na.rm = T
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```{r Math}
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### Math ###
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Math_subset_Low <- TSR_data[TSR_data$InterestedinstudyingMath < 3 & TSR_data$InterestedinstudyingMathy != 0, ]
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Math_subset_Low <- TSR_data[TSR_data$InterestedinstudyingMath < 3 & TSR_data$InterestedinstudyingMath != 0, ]
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Math_subset_High <- TSR_data[TSR_data$InterestedinstudyingMath > 3, ]
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@ -462,7 +472,7 @@ Math_subset_High <- TSR_data[TSR_data$InterestedinstudyingMath > 3, ]
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#Low interest in Math
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mean(as.numeric(Math_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Math
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mean(as.numeric(Math_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Math_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Math
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@ -481,7 +491,7 @@ CompSci_subset_High <- TSR_data[TSR_data$InterestedinstudyingComputerScience > 3
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#Low interest in Computer Science
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mean(as.numeric(CompSci_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Computer Science
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mean(as.numeric(CompSci_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(CompSci_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Computer Science
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@ -500,7 +510,7 @@ Busi_subset_High <- TSR_data[TSR_data$InterestedinstudyingBusiness > 3, ]
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#Low interest in Business
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mean(as.numeric(Busi_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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#High interest in Business
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mean(as.numeric(Busi_subset_Low$InterestedinstudyingTheology), na.rm = TRUE)
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mean(as.numeric(Busi_subset_High$InterestedinstudyingTheology), na.rm = TRUE)
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## Religious Studies Interest
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#Low interest in Business
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@ -514,6 +524,15 @@ mean(as.numeric(Busi_subset_High$InterestedinstudyingReligiousStudies), na.rm =
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## Mean Knowledge in Theology and Religious Studies by High/Low Subject Knowledge
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```{r Philosophy}
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# Base calculations
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mean(as.numeric(TSR_data$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(TSR_data$GoodunderstandingofReligiousStudies), na.rm = TRUE)
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mean(as.numeric(TSR_data$GoodunderstandingofPhilosophy), na.rm = TRUE)
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mean(as.numeric(TSR_data$GoodunderstandingofPsychology), na.rm = TRUE)
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mean(as.numeric(TSR_data$GoodunderstandingofEnglish), na.rm = TRUE)
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mean(as.numeric(TSR_data$GoodunderstandingofMath), na.rm = TRUE)
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### Philosophy ###
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# Low understanding of philosophy cohort
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@ -526,7 +545,7 @@ Philos_subset_High <- TSR_data[TSR_data$GoodunderstandingofPhilosophy > 3, ]
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#Low knowledge in Philosophy
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mean(as.numeric(Philos_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Philosophy
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mean(as.numeric(Philos_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Philos_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies Knowledge
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#Low knowledge in Philosophy
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@ -545,7 +564,7 @@ Soc_subset_High <- TSR_data[TSR_data$GoodunderstandingofSociology > 3, ]
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#Low knowledge in Sociology
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mean(as.numeric(Soc_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Sociology
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mean(as.numeric(Soc_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Soc_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Sociology
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@ -564,7 +583,7 @@ Psych_subset_High <- TSR_data[TSR_data$GoodunderstandingofPsychology > 3, ]
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#Low knowledge in Psychology
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mean(as.numeric(Psych_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Psychology
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mean(as.numeric(Psych_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Psych_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Psychology
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@ -583,7 +602,7 @@ Hist_subset_High <- TSR_data[TSR_data$GoodunderstandingofHistory > 3, ]
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#Low knowledge in History
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mean(as.numeric(Hist_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in History
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mean(as.numeric(Hist_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Hist_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in History
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@ -602,7 +621,7 @@ Ethics_subset_High <- TSR_data[TSR_data$GoodunderstandingofEthics > 3, ]
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#Low knowledge in Ethics
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mean(as.numeric(Ethics_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Ethics
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mean(as.numeric(Ethics_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Ethics_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Ethics
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@ -621,7 +640,7 @@ Polit_subset_High <- TSR_data[TSR_data$GoodunderstandingofPolitics > 3, ]
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#Low knowledge in Politics
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mean(as.numeric(Polit_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Politics
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mean(as.numeric(Polit_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Polit_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Politics
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@ -640,7 +659,7 @@ Eng_subset_High <- TSR_data[TSR_data$GoodunderstandingofEnglish > 3, ]
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#Low knowledge in English
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mean(as.numeric(Eng_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in English
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mean(as.numeric(Eng_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Eng_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in English
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@ -659,7 +678,7 @@ Math_subset_High <- TSR_data[TSR_data$GoodunderstandingofMath > 3, ]
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#Low knowledge in Math
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mean(as.numeric(Math_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Math
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mean(as.numeric(Math_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Math_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Math
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@ -678,7 +697,7 @@ CompSci_subset_High <- TSR_data[TSR_data$GoodunderstandingofComputerScience > 3,
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#Low knowledge in Computer Science
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mean(as.numeric(CompSci_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Computer Science
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mean(as.numeric(CompSci_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(CompSci_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Computer Science
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@ -697,7 +716,7 @@ Busi_subset_High <- TSR_data[TSR_data$GoodunderstandingofBusiness > 3, ]
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#Low knowledge in Business
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mean(as.numeric(Busi_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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#High knowledge in Business
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mean(as.numeric(Busi_subset_Low$GoodunderstandingofTheology), na.rm = TRUE)
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mean(as.numeric(Busi_subset_High$GoodunderstandingofTheology), na.rm = TRUE)
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## Religious Studies knowledge
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#Low knowledge in Business
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@ -711,6 +730,17 @@ mean(as.numeric(Busi_subset_High$GoodunderstandingofReligiousStudies), na.rm = T
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## Mean Employability in Theology and Religious Studies by High/Low Subject Employability
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```{r Philosophy}
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# Base Calculations
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mean(as.numeric(TSR_data$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$ReligiousStudiesemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$Philosophyemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$PsychologyEmployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$Englishemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$Mathemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$Businessemployability), na.rm = TRUE)
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mean(as.numeric(TSR_data$ComputerScienceemployability), na.rm = TRUE)
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### Philosophy ###
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Philos_subset_Low <- TSR_data[TSR_data$Philosophyemployability < 3 & TSR_data$Philosophyemployability != 0, ]
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@ -720,7 +750,7 @@ Philos_subset_High <- TSR_data[TSR_data$Philosophyemployability > 3, ]
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#Low employability in Philosophy
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mean(as.numeric(Philos_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Philosophy
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mean(as.numeric(Philos_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Philos_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Philosophy
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@ -739,7 +769,7 @@ Soc_subset_High <- TSR_data[TSR_data$Sociologyemployability > 3, ]
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#Low employability in Sociology
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mean(as.numeric(Soc_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Sociology
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mean(as.numeric(Soc_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Soc_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Sociology
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@ -758,7 +788,7 @@ Psych_subset_High <- TSR_data[TSR_data$PsychologyEmployability > 3, ]
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#Low employability in Psychology
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mean(as.numeric(Psych_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Psychology
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mean(as.numeric(Psych_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Psych_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Psychology
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@ -777,7 +807,7 @@ Hist_subset_High <- TSR_data[TSR_data$Historyemployability > 3, ]
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#Low employability in History
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mean(as.numeric(Hist_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in History
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mean(as.numeric(Hist_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Hist_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in History
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@ -796,7 +826,7 @@ Ethics_subset_High <- TSR_data[TSR_data$Ethicsemployability > 3, ]
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#Low employability in Ethics
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mean(as.numeric(Ethics_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Ethics
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mean(as.numeric(Ethics_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Ethics_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Ethics
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@ -815,7 +845,7 @@ Polit_subset_High <- TSR_data[TSR_data$Politicsemployability > 3, ]
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#Low employability in Politics
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mean(as.numeric(Polit_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Politics
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mean(as.numeric(Polit_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Polit_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Politics
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@ -834,7 +864,7 @@ Eng_subset_High <- TSR_data[TSR_data$Englishemployability > 3, ]
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#Low employability in English
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mean(as.numeric(Eng_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in English
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mean(as.numeric(Eng_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Eng_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in English
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@ -853,7 +883,7 @@ Math_subset_High <- TSR_data[TSR_data$Mathemployability > 3, ]
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#Low employability in Math
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mean(as.numeric(Math_subset_Low$Theologyemployability), na.rm = TRUE)
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#High employability in Math
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mean(as.numeric(Math_subset_Low$Theologyemployability), na.rm = TRUE)
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mean(as.numeric(Math_subset_High$Theologyemployability), na.rm = TRUE)
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## Religious Studies employability
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#Low employability in Math
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@ -872,7 +902,7 @@ CompSci_subset_High <- TSR_data[TSR_data$ComputerScienceemployability > 3, ]
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#Low employability in Computer Science
|
||||
mean(as.numeric(CompSci_subset_Low$Theologyemployability), na.rm = TRUE)
|
||||
#High employability in Computer Science
|
||||
mean(as.numeric(CompSci_subset_Low$Theologyemployability), na.rm = TRUE)
|
||||
mean(as.numeric(CompSci_subset_High$Theologyemployability), na.rm = TRUE)
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||||
|
||||
## Religious Studies employability
|
||||
#Low employability in Computer Science
|
||||
|
|
@ -891,7 +921,7 @@ Busi_subset_High <- TSR_data[TSR_data$Businessemployability > 3, ]
|
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#Low employability in Business
|
||||
mean(as.numeric(Busi_subset_Low$Theologyemployability), na.rm = TRUE)
|
||||
#High employability in Business
|
||||
mean(as.numeric(Busi_subset_Low$Theologyemployability), na.rm = TRUE)
|
||||
mean(as.numeric(Busi_subset_High$Theologyemployability), na.rm = TRUE)
|
||||
|
||||
## Religious Studies employability
|
||||
#Low employability in Business
|
||||
|
|
|
|||
Loading…
Reference in a new issue