re_connect_survey/Connect Project R Markdown.Rmd

---
title: "Connect Project"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.

When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

```{r cars}
summary(cars)
```

## Including Plots

You can also embed plots, for example:

```{r pressure, echo=FALSE}
plot(pressure)
```

Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.

### To Do List

## Upload Data
```{r Data Upload}
connect_data = read.csv("connectDATA.csv")
```

## Summary of Data
Data summary/visualisation with subsetting:
  - RH: display simple summary of data (bar/pie chart) to Q25/26, Q3
  
```{r Frequencies}  
#Frequencies#
  
Q25_frequencies = table(connect_data$Q25)
Q25_frequencies
Q26_freq = table(connect_data$Q26)
Q26_freq
Q3_freq = table(connect_data$Q3)
Q3_freq

#test3 = as.factor(connect_data$Q3, levels = c(1, 2, 3, 4, 5), labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
```

```{r Q25 bar/pie}
pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))

```

pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
  # rough draft of piechart

```{r Q26 bar/pie}
```

pie(Q26_freq) 
  #very messy as a pie chart - split by type? Or is it important to see crossover

```{r Q3 bar/pie}

Q3_data <- read.csv("Q3.csv")

```


pie(Q3_freq)
  #also not optimal as pie...perhaps bar



  - RH: display summaries of responses to key questions for Q22 (syllabus evaluation), Q23, Q24, Q25, Q26, Q27, with subsetting by:
    - Q8 (school type)
    - Q9 (school size)
    - Q10 (school location)
    - Q1 (grade level) + Q35 (teaching role) + +Q5 (teaching proportion) Q2 (tenure) + and Q3 (subjects taught), + Q6/Q7 (management)
    - Q12-14 (school's official religion) / Q15-16 (school's informal religion)
    - Q21 (respondent personal religious background)
    - Q4 (teacher's degree subject)
    - Q18 (respondent gender)
    - Q19 (respondent ethnic self-desc)
    
```{r Plots}
# Q22

# Q23

# Q24

# Q25

# Q26

# Q27
```

## Correlation testing:
  - RH: test for correlation between "social issue" box ticked on Q20 and responses to Q22, Q23, Q27 
  
  - Make Q20 a factor with 14 levels
  - Collapse 2 Q22 columns into one mean for analyses
  - Analyse 1 way anova Q20 (14 levels) by Q22; Q23[1-2]; Q27[1-7] 
  

```{r Correlation 1}

```
  - RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q24, Q25, Q27, Q30