Goal of our work

We took the dataset on UA in 2012 to do research about how people evaluate their goverment and actions of politicians. The future work will be a comparison of these attitudes between different years to show changes. Maybe later we even can say about how Maydan evolve - because of people (if their attitudes changed to worse) or it was created artificially by someone (if attitudes of people didn’t change).

Now we want to describe one particular dataset to show the variables that we need in our work:

Describing variables

Variable Qualitative_or_Quantitative Level_of_measurement Continuous_or_Discrete
polintr: How interested in politics Quantitative Ordinal Discrete
trstprl: Trust in countrys parliament Quantitative Ordinal Discrete
trstlgl: Trust in the legal system Quantitative Ordinal Discrete
trstplc: Trust in the police Quantitative Ordinal Discrete
trstplt: Trust in politicians Quantitative Ordinal Discrete
trstprt: Trust in political parties Quantitative Ordinal Discrete
vote: Voted last national election Quantitative Ordinal Discrete
contplt: Contacted politician or government official last 12 months Quantitative Ordinal Discrete
pbldmn: Taken part in lawful public demonstration last 12 months Quantitative Ordinal Discrete
implvdm: How important for you to live in democratically governed country Quantitative Ordinal Discrete
dmcntov: How democratic [country] is overall Quantitative Ordinal Discrete
stflife: How satisfied with life as a whole Quantitative Ordinal Discrete
stfgov: How satisfied with the national government Quantitative Ordinal Discrete

Working with the data

Fisrt step - upload the ESS6UA dataset to the environment and create a new data set to more comfortable work with only those variables that we need:

getwd()
## [1] "/students/dstsimokha/DA_shirokaner"
politics = haven::read_sav("ESS6UA.sav")
politics <- dplyr::select(politics, polintr, trstprl, trstlgl, trstplc, trstplt, trstprt, vote, contplt, pbldmn, implvdm, dmcntov, stflife, stfgov)

politics <- na.omit(politics)

Second step - downloading packages that we need in our work.

library(ggplot2)
library(dplyr)
library(knitr)
library(rmarkdown)

Also add the “Mode” function to build graphs.

Mode <- function(x) {
  ux <- unique(x)
  ux[which.max(tabulate(match(x, ux)))]
}

Table statistics on single variables

##     polintr         trstprl          trstlgl          trstplc      
##  Min.   :1.000   Min.   : 0.000   Min.   : 0.000   Min.   : 0.000  
##  1st Qu.:2.000   1st Qu.: 0.000   1st Qu.: 0.000   1st Qu.: 0.000  
##  Median :3.000   Median : 1.000   Median : 1.000   Median : 1.000  
##  Mean   :2.787   Mean   : 1.776   Mean   : 1.786   Mean   : 1.922  
##  3rd Qu.:3.000   3rd Qu.: 3.000   3rd Qu.: 3.000   3rd Qu.: 3.000  
##  Max.   :4.000   Max.   :10.000   Max.   :10.000   Max.   :10.000  
##     trstplt          trstprt            vote          contplt     
##  Min.   : 0.000   Min.   : 0.000   Min.   :1.000   Min.   :1.000  
##  1st Qu.: 0.000   1st Qu.: 0.000   1st Qu.:1.000   1st Qu.:2.000  
##  Median : 1.000   Median : 1.000   Median :1.000   Median :2.000  
##  Mean   : 1.719   Mean   : 1.908   Mean   :1.245   Mean   :1.921  
##  3rd Qu.: 3.000   3rd Qu.: 3.000   3rd Qu.:1.000   3rd Qu.:2.000  
##  Max.   :10.000   Max.   :10.000   Max.   :3.000   Max.   :2.000  
##      pbldmn         implvdm          dmcntov          stflife      
##  Min.   :1.000   Min.   : 0.000   Min.   : 0.000   Min.   : 0.000  
##  1st Qu.:2.000   1st Qu.: 6.000   1st Qu.: 2.000   1st Qu.: 3.000  
##  Median :2.000   Median : 8.000   Median : 4.000   Median : 5.000  
##  Mean   :1.975   Mean   : 7.373   Mean   : 4.002   Mean   : 4.996  
##  3rd Qu.:2.000   3rd Qu.:10.000   3rd Qu.: 6.000   3rd Qu.: 7.000  
##  Max.   :2.000   Max.   :10.000   Max.   :10.000   Max.   :10.000  
##      stfgov     
##  Min.   : 0.00  
##  1st Qu.: 1.00  
##  Median : 2.00  
##  Mean   : 2.45  
##  3rd Qu.: 4.00  
##  Max.   :10.00

Single variables with central tendency measures

This chart illustrates how many people in Ukraine trust in the parliament, where trust varies from 0- not trust at all to 10-complete trust. According to this graph, we can conclude that in average (mean is red) ukrainians do not trust in parliament. The median (is blue) is in the left side, we can say that there were people who trust in the lowest level or do not trust at all.

This graph shows the level of importance democratic regimes for ukrainian people, where importance varies from 0- Not at all important to 10- Extremely important. In average democracy is important for people. Lots of people conclude that democracy is significantly important.

Meaningful binary combinations of variables - categorical by categorical

On these boxplots we can see the corelation between life-satisfaction and evaluation of democracy in country - we need to know more about it and prove this corelation with statistical tests.

This graph is really complicated and shows us that people who voted in the last election and less satisfied with the national goverment attend to public demostrations more

In conclusion we want to notice that this work can will be really important in researchs about how revolutions are evolving and they are created by people’s will or artificially by some small group of people.