Exam content 1

• Key characteristics of normal distribution


  Symmetry: Imagine a normal distribution as a balanced see-saw, where the left side is just like the right side. Picture folding the see-saw in half at the middle, and both halves would match up perfectly.

  
  

  Central tendency: If a single value describes the centre of the data then that means central tendency. Mean. mode, and median.
• Key characteristics of normal distribution


  Standard deviation: This tells you the average spread of the data values from the mean data.

  
  

  Empirical rule: This rule is like a guide telling us where most of the kids in our group hang out. It says roughly 68% of the kids are within arm's reach from the average kid, 95% are within a couple of steps, and 99% are within a short jog away.
• When a distribution is not normal


  Different Data Patterns: Sometimes, data doesn't follow the regular patterns we expect. That's normal! Real-life situations can show various kinds of patterns, and that's okay.

  
  

  Uneven data, such as uneven distribution of income, can cause a graph to tilt to one side, resulting in positive skewness, where most people earn a small amount while a few earn significantly more.
• Positivism


  Positivism says that we truly understand things when we see them clearly with our senses. For example, in sociology, it means studying things we can see and measure, like how many crimes happen or how people vote.

  
  

  Positivism believes theories should be tested with experiments and observations. By doing this, we try to find rules or patterns that explain what we see.

  
  

  It also says that knowledge comes from observing real things. Scientists hope to find patterns by watching and collecting data, which helps them make general rules.
• Subjectivism


  Interpretivism is a way of thinking that says the way people interact and behave socially is different from how things work in nature.

  
  

  It argues that regular science methods aren't enough to understand human behavior and society. Instead, it suggests using different methods to study social stuff.

  
  

  This way of thinking focuses on figuring out why people do stuff and what it means to them. For example, in a research project, they might talk to people to figure out why they do certain things and what those actions mean to them.
• Focus groups


  Focus groups are a type of qualitative research that uses a group of 6-10 individuals, often 8, to investigate and debate a topic.

  
  

  These groups provide insights into consumer decisions, products and services, and heated topics.

  
  

  They offer deeper and more natural feedback than individual interviews and are easier to plan than experiments or large-scale surveys.
• Focus groups (Advantages)


  When people discuss together, they can share lots of different thoughts and experiences. This can help us learn more about a topic than just talking to one person at a time.

  
  

  In focus groups, people can come up with fresh thoughts and viewpoints that the researcher might not have thought about before. As they talk, they can build on each other's ideas, which helps us understand things better.

  
  

  Focus groups are cheaper than doing interviews with each person separately. You can talk to many people at once, so you get more information without spending as much.
• Focus groups (Disadvantages)


  Focus groups cover a lot of different views, but they might not let us really explore each person's experiences deeply. Because of time limits and how the group works together, people might not get to share everything.

  
  

  Some people might talk a lot and take over the conversation, while others stay quiet. A good leader is important to make sure everyone gets a chance to speak up.

  
  

  In focus groups, people might all agree with each other just to fit in, even if they really don't.
• Reflexivity


  "Reflexivity" means being aware of yourself as a researcher.

  
  

  It's about recognizing how your own experiences, biases, and background might affect how you do the research and understand the results.

  
  

  By thinking about these things, you can try to reduce their influence and make sure you present the data in a fair way.
• Flexibility 


  Qualitative research is about figuring out complicated social stuff by digging deep.

  
  

  Unlike counting things in quantitative research, qualitative studies are open to new ideas and important topics that come up.

  
  

  Being flexible means the researcher can change their plan as they go.

  
  

  This could mean tweaking interview questions, exploring interesting side topics that come up during research, or even shifting the focus of the study completely if a new idea seems better.
• Descriptive coding


  Descriptive coding is a method used to identify and name the main topics in qualitative data, such as customer feedback on a new product.

  
  

  It helps organize the data and makes it easier to handle large amounts of text. Descriptive codes are based on the participants' experiences and words, rather than predetermined categories.

  
  

  1. Summarizes data: Condenses data into concise labels or codes.
  2. Initial stage: Often the first step in qualitative analysis, setting