This course is designed to get you working with data related to crime and criminal justice, as well as other aspects of everyday life. It is meant to be both fun, and a lot of hard work, as you will be acquiring a new skill. The teaching team are here to help you make this enjoyable, and we guarantee that as long as you put in the effort, you will find this course easy. Nothing we teach you requires any sort of previous knowledge or special disposition towards maths or stats, instead all you will need is an inquiring mind, and a willingness to learn. Your main job is to do all the reading, watch all the videos, ask questions, follow all the tasks and activities, try new things, make mistakes, get feedback, ask questions, ask for help, help each other, ask questions, ask for help, ask questions. If you get stuck anywhere do not suffer in silence. Our job here is to make sure that you engage with the topic and make this course work for you, so help us do this by keeping up, and asking for help when you fall behind.
Imagine you assembled an extensive library comprised of the finest literary works in the world. How valuable would it be to someone who is illiterate? Until they can read and appreciate it, the library remains just a useless collection of inked paper. Similarly, all of the rich data visualizations and intelligence built into today’s self-service analytics tools can be negated by a simple deficiency in data literacy, which can be defined as the ability to understand, use and communicate data effectively. Increasingly, this data literacy divide will impede organizations of all shapes and sizes from reaping higher rewards from their data investments.
Every day more and more data are being generated about the world arouns us. It is important that we posess the ability to make sense of these data, and to use them to draw meaningful conclusions about the phenomena in which we are interested.
The UK has a shortage of social scientists trained in quantitative methods and consequently is unable to meet the demand from employers across all sectors – academia, government, charities and business – for staff who can apply such methods to evaluating evidence and analysing data
In fact, recent numbers show that About 4 in 5 UK adults have low numeracy levels which costs the UK £billions.
So not only is this a vital skill, it is one that will (for now) give you a competitive advantage in your employability. Doing well in this course and it’s 2nd term counterpart, Modelling Criminological Data also opens up the possibility to parttake in a Q-step internship. These things are really cool - you get placed with an organisation such as the Home Office, or College of Policing, or more, work on an interesting project, and get paid. Pretty nice way to spend a month or so of your summer. You will hear more about these but some detail is available on the Q-step website
This course will put you on the right track to acquiring the transferable skills that make you employable in the field of data analysis, which has plenty of jobs in criminal justice. You could for example consider a career as a Criminal Intelligence Analyst. But there are many many other options as well, and currently there are more jobs than people to fill them. In fact, you may have heard some myths about how data science is the sexiest job of the 21st century. This is not true. Firefighting is obviously sexier, since that’s where the calendars come from.. Nevertheless, data is EVERYWHERE. And as responsible citizens there is an expectation of data literacy placed upon you by our current circumstances. No matter the job you end up in, it is very likely that you will have contact with some form of data. At the very least you will be a consumer of data through reading/ watching the news. And it’s important that you understand what you see.
This course is designed to make you data literate criminologists, who can not only consume data in an informed manner, use it as evidence to support your arguments, or to question those made by others, and draw meaningful conclusions from the ever-increasing firehose of data being generated in our domain.
Lab sessions - 20 hours: The course will consist of lab sessions, where students will be expected to work through previously constructed readings, videos, and exercises, while recieving support from the teaching staff. Students will be able to work individually and move through the course materials at their own pace, while also coming together occasionally in group-based tasks and activities. Attendance at these sessions is mandatory and monitored
Lectures - 10 hours: There will be weekly Lectures which will take the form of interactive lectures, where sometimes students can receive feedback on their work, and ask questions. General concepts will be clarified, and students will be able to use this opportunity to catch up, and ensure their learning.
The course hopes to achieve the following aims:
Identify the principal data sources for a number of key areas in criminology and other cognate areas of social policy
Demonstrate a critical awareness of key data quality issues
Read and interpret quantitative information in the form of tables and graphs
Understand some of the basic principles underlying statistical analysis including: samples and populations, distributions, statistical significance, hypothesis testing
Understand the different levels at which social characteristics (variables) area measured and how resulting data are distributed
Become aware of the range of existing qualitative data and basic approaches to their analysis
Be in a position to consider conducting secondary data analysis for their third year UG dissertations (after taking Modelling Criminological data in their 2nd term).
Teaching methods will combine lab sessions, lectures, group discussion, interactive teaching and private study. Each week we will have a two-hour lab session and a feedback workshop to discuss homework solutions and to clarify understanding. We used something close to the “flip teaching” method. This means that there is a greater expectation that you will come prepared to class (i.e., have done the required reading) and it also means that you will spend most of the contact time working through a set of computer exercises trying to put to practice the knowledge acquired through your reading. YOU HAVE TO DO THE READING BEFORE YOU COME TO THE LAB SESSION. The course will not work for you otherwise.
The two-hour lab sessions run from week 1 to week 10. Lab sessions will introduce you to some of the principles and the concepts underlying our use of software for data analysis. During the lab period, students will work on computing exercises to develop and test their understanding of the material presented online. The course coordinator and the teaching assistants will help you to resolve problems in dealing with the software and the interpretation of results.
Although there won’t be much formal lecturing during most of the lab sessions, the materials you will be provided during these interactive sessions will contain hyperlinks to video presentations or reading material that you will be able to consult for further conceptual clarification of the topics being explored. The computer clusters do not have headphones attached to the computers. Therefore, you are strongly recommended to bring your own headphones so that you can watch (and listen to) these videos during the lab sessions.
From week 1 to 10 of the semester we will have one-hour Feedback Support Sessions. These sessions will focus on explaining the answers to the previous week homework and further clarifying concepts.
Homework 20%. Short homework exercises will be assigned every week, to be submitted either through Blackboard, or through presentation in the Lecture.
Final project 80%. Students will be required to produce a report of 2,500 words incorporating charts, tables and graphs, to be produced to a good quality standard.
Each week, homework will be assigned for students to work on in their own time. This homework will be handed in and assessed. Total scores for all homework submitted over the course will make up 20% of the mark for the course unit. Weekly (compulsory) Lectures allow students to get formative feedback on homework after having handed it in, helping them to determine how well they have understood the material. The Lecture is designed for students to be able to review their weekly progress with a tutor.
None
-Labs 20
-Lectures 10
Your course director is Dr Reka Solymosi. Call her Reka. If that makes you uncomfortable then Dr Solymosi. Don’t call her Ms/Mrs Solymosi, that’s her mum. Don’t call her ‘hey’/ ‘yo’, each time that happens a she grows a new grey hair, and it makes her sad. You can reach her via email at reka.solymosi@manchester.ac.uk.
For two weeks (when you are learning about qualitative research) your lecturer will be Dr Nicholas Lord. You can reach him at nicholas.lord@manchester.ac.uk.
Your teaching assistants are:
Check the syllabus. Then check the discussion board. If your question is already answered on either of these forums it’s the fastest reply you can get. To ask questions about the course content, the assessment, the reading, blackboard, anything like this post on the BB discussion board. If for some reason you’re uncomfortable doing so, please email the entire teaching team cc-d who will post the question for you. This adds an extra step so please keep in mind taking this option will add delay to you receiving an answer. Please check the discussion board for a posted answer. If your question is personal in nature, and is not relevant to others, then do email the teaching team in one email together.
Email the entire teaching team together please. This is your 2nd best option for fast replies. Our emails are: Reka.solymosi@manchester.ac.uk
You can subscribe to a discussion board so that you receive a notification each time a post is made. Watch this video https://www.youtube.com/watch?v=xGLtjrhG3RA to see how.
If you miss a lab try to catch up on it in your own time. Whenever you have a question or want clarification, make a note as you go through. If you can, check the blackboard discussion forum to see if this has been answered, and if no, post your question there. You can also book office hours to come and ask your questions there, or bring them to the next lab which you can attend. Labs are attendance monitored so you must get in touch with TLSEO to excuse your absence.
Lectures are podcast and immediately released so you can watch a lecture after it’s finished. Just like with labs, whenever you have a question or want clarification, make a note as you go through. If you can, check the blackboard discussion forum to see if this has been answered, and if no, post your question there. You can also book office hours to come and ask your questions there, or bring them to the next lab which you can attend.
Before you start your quiz please make sure you have your reading notes and completed tasks in front of you. Make sure you have 30 min of uninterrupted time with good Internet connection, on a charged computer. Do not ever press the back or refresh buttons. That said, stuff happens, so each student gets one “get out of homework free” card. You can use this once to discount one homework from your grade in the event of something going wrong. You cannot use this to discount a quiz only because you’re unhappy with the grade though, this is a last resort option, don’t try to game it please. You can find the card on Blackboard under the homework section.
If you think that you gave a correct answer, but quiz marked it wrong, please email REKA with the email subject QUIZ and tell me 1: who you are (with student number) 2: the quiz number and question description 3: your answer and why you think it’s correct. I willing reply to you about it in 2 working days.
Our office hours can be found on Blackboard page under the communications tab
One option is to use a screen reader. This is something that can read text to you out loud. You should bring headphones to class if you are going to use this option. One example is a chrome plugin caller Read Aloud. You can follow the instructions from the link to install this to your Chrome browser, and then use it to read aloud the lab notes to you (if you have opened them in Chrome). Similar software is available for other browsers as well.