6  Mock questions

7 Mock Test

Before starting it’s good to get some of the preliminary steps taken care of first. In this case, we first download the data, and then clear the workspace to get rid of older variables that may be in our environment area since last working with RStudio. Finally, we import the libraries that we will be using.

7.1 Data download

Some of the datasets on Canvas have been updated, so please re-download the data.

  • world_value_survey - Located in Week 3

  • LAD December 2021 EW BUC.geojson - Located in Week 4

  • Census_2021_Wards.csv - Located in Week 4

  • Census_2021_Districts.csv - Located in Week 4

7.2 Clear the workspace

This is important because you could be using an older dataset that is incorrect if you don’t do this.

rm(list = ls())

7.3 Load libraries

These are the libraries that will use be using for the mock test. The specific libraries to be loaded will depend on the specific task to be completed. However, these are the most common ones.

library(tidyverse)
library(sf)
library(tmap)
library(ineq)

This mock exam consists of a series of 25 questions. Many of these questions are from the labs, so be sure to go through these before the final exam. Your final exam will have 20 questions and will be multiple choice. Unless told otherwise in the exam, you will be expected to write code (i.e., copy and paste from labs and modify accordingly) to derive results, which you will then use to determine to correct answer from a set of multiple choice options. You are not expected to write code from scratch.

7.4 Question 1

Write code to load the world_value_survey.csv dataset into RStudio. How many rows and columns does this dataset have? 

7.5 Question 2

Write code to load the Census_2021_Wards.csv dataset into RStudio. Calculate the total sum of the variable Worker across all wards in the dataset. 

7.6 Question 3

Find the min value of variable Density in the Wards dataset without code.

7.7 Question 4

Write code to identify the ward with the min value for the for the variable Mean_Age using the Census_2021_Wards dataset.

7.8 Question 5

Write code to compute the overall proportion of workers who work from home (variable: Work_from_Home) to the total works (variable: Worker) in the Census_2021_Wards dataset.

7.9 Question 6

Write code to generate a statistical summary of the variable Social_Rented using the Census_2021_Wards.csv dataset. From the output, identify and report the mean value of Social_Rented. 

7.10 Question 7

Write code to produce a frequency table of the variable religion using the world_value_survey dataset. How many correspondents have a religion type of “Muslim”? What is the proportion of that to the whole survey sample?

7.11 Question 8

Write code to create boxplots of variable Extractive_Job, Productive_Job, Professional, Routine_Job using the Census_2021_Wards dataset.  Based on your plotst, which variable shows the most positively skewed distribution? (Recall: a positively skewed boxplot has a longer upper whisker and the median positioned closer to the lower quartile.) How to interpret the result?

7.12 Question 9

Write code to compute mean and standard deviation of variables Disabled and Poor_Health in the Census_2021_Wards.csv dataset in R. Compare and interpret the results for both variables

7.13 Question 10

Write code to compare the life satisfaction (variable: life_satisfaction) between different marital status (variable: marital_status) using the world_value_survey.csv dataset using boxplots. Interpret the findings?

7.14 Question 11

The age in the real world is always a normal distribution. We assume that the age in the World Value Survey is also normal distribution. Write code to calculate the mean and standard deviation of age using the world_value_survey.csv dataset. Based on your output, use the 68-95-97.5 rule to interpret the result.

7.15 Question 12

Write code to compute the standard error of the mean proportion for work status as Housewife. (variable: work_status, category: Housewife) across all observations in the World Value Survey dataset (world_value_survey.csv). What is the approximate result?

7.16 Question 13

Write code to compute the mean value and 95% confidence interval of the life_satisfaction variable in the World Value Survey (world_value_survey.csv).

7.17 Question 14

Write code to produce a cross-tabulation of settlement type (variable: settlement_type) by how they feel related to the world (variable: relate_to_world) using the world_value_survey.csv dataset. According to your table, 

Based on your results, which type of settlement has the highest mean proportion of feeling very close to the world?

7.18 Question 15

What is the Standard Error of samples? With the increase of sample, how will Standard Error change?

7.19 Question 16

You are required to write code to combine two datasets, LAD December 2021 EW BUC.geojson and Wards_2021_Districts.csv, using a left join. Both datasets contain a common variable called LAD21CD, which is the unique code assigned by the Office for National Statistics (ONS) to each local authority district in the 2021 Census. This variable should be used to match the two datasets correctly. After joining the datasets, use the combined data to create a map showing the percentage of self-employed people at the district level across the UK.

7.20 Question 17

Write code to create a scatterplot showing the relationship between the variables Density and Born_in_UK using the Census_2021_Districts.csv dataset. Make sure that Density is shown on the x-axis and Born_in_UK is shown on the y-axis.

7.21 Question 18

Write code to calculate the appropriate correlation coefficient between the variables Mean_Age and Poor_Health using the Census_2021_Wards.csv dataset. Please also interpret what the resulting value mean.

7.22 Question 19

Write code to create a barplot showing the relationship between the variables marital_status and happiness using the world_value_survey.csv dataset. What pattern(s) can be observed?

7.23 Question 20

When trying to understand the skewness of a variable, why is it important to use both visualisations and skewness metrics?

7.24 Question 21

Write code to calculate the Gini coefficient between the variables Poor_Health using the Census_2021_Wards.csv dataset. Be sure to not include an NA values. Please also interpret what the resulting value mean.

7.25 Question 22

Compute the Spearman’s rank correlation coefficient between the numeric variable Self_Employed (equivalent net pay) and the other numeric variables in the Census_2021_Wards.csv dataset, along with their associated p-values. Based on your results, interpret what do they mean in the context of the association between Self_Employed and Married and its p-value?

7.26 Question 23

Write code to plot the Lorenz curve for the variable Density using the Census_2021_Wards.csv dataset. Please interpret what the resulting value mean.

7.27 Question 24

Write code to compute the skewness for the variable Density using the Census_2021_Wards.csv dataset. Please interpret what the resulting value mean.

7.28 Question 25

In addition to the p-value, we can also calculate the confidence intervals for the correlation between two variables. Why are confidence intervals useful in this case?