mirror of
https://github.com/kidwellj/re_connect_survey.git
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a14e1fde4c
Cleaned datafile more for analysis and ease of viewing (changed text to numbers for Q25, Q26, Q3 in order to create frequency tables for pie charts and bar graphs). Preliminary checking of pie chart and bar graph for frequencies Notes on how to analyze responses in last section (ANOVA)
113 lines
2.8 KiB
Plaintext
113 lines
2.8 KiB
Plaintext
---
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title: "Connect Project"
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output: html_document
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = TRUE)
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```
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## R Markdown
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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>.
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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:
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```{r cars}
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summary(cars)
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```
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## Including Plots
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You can also embed plots, for example:
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```{r pressure, echo=FALSE}
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plot(pressure)
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```
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Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
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### To Do List
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## Upload Data
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```{r Data Upload}
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connect_data = read.csv("connectDATA.csv")
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```
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## Summary of Data
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Data summary/visualisation with subsetting:
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- RH: display simple summary of data (bar/pie chart) to Q25/26, Q3
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```{r Frequencies}
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#Frequencies#
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Q25_frequencies = table(connect_data$Q25)
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Q25_frequencies
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Q26_freq = table(connect_data$Q26)
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Q26_freq
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Q3_freq = table(connect_data$Q3)
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Q3_freq
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#test3 = as.factor(connect_data$Q3, levels = c(1, 2, 3, 4, 5), labels = c("Worldviews", "Religion", "Theology", "Ethics", "Philosophy"))
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```
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```{r Q25 bar/pie}
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pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
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```
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pie(Q25_frequencies, labels = c("Maybe", "No", "Yes"))
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# rough draft of piechart
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```{r Q26 bar/pie}
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```
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pie(Q26_freq)
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#very messy as a pie chart - split by type? Or is it important to see crossover
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```{r Q3 bar/pie}
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```
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pie(Q3_freq)
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#also not optimal as pie...perhaps bar
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- RH: display summaries of responses to key questions for Q22 (syllabus evaluation), Q23, Q24, Q25, Q26, Q27, with subsetting by:
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- Q8 (school type)
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- Q9 (school size)
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- Q10 (school location)
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- Q1 (grade level) + Q35 (teaching role) + +Q5 (teaching proportion) Q2 (tenure) + and Q3 (subjects taught), + Q6/Q7 (management)
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- Q12-14 (school's official religion) / Q15-16 (school's informal religion)
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- Q21 (respondent personal religious background)
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- Q4 (teacher's degree subject)
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- Q18 (respondent gender)
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- Q19 (respondent ethnic self-desc)
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```{r Plots}
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# Q22
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# Q23
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# Q24
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# Q25
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# Q26
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# Q27
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```
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## Correlation testing:
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- RH: test for correlation between "social issue" box ticked on Q20 and responses to Q22, Q23, Q27
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- Make Q20 a factor with 14 levels
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- Collapse 2 Q22 columns into one mean for analyses
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- Analyse 1 way anova Q20 (14 levels) by Q22; Q23[1-2]; Q27[1-7]
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```{r Correlation 1}
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```
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- RH: test for correlation between responses to religion questions: Q12-14, Q15-16 and Q21 and responses to Q22, Q23, Q24, Q25, Q27, Q30
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