Data collected in original form is called raw data
Data can be classified into two types
- Categorical data: Qualitative data, usually collected through observation and is descriptive. E.g. colour, texture, etc.
- Numerical data: Quantitative data consisting of numerical values.
There are 2 types of numerical data:
- Discreet data:
- It is data based on counts, it is data that can be associated with a specific value.
- Bar graph represents discreet data only
- Continuous data:
- Data representing series of values or values grouped into categories.
- Histogram represents continuous data.
A frequency distribution is the organisation of raw data in table form, using classes and frequencies.
The data can be placed in categories and organized in categorical frequency distributions.
- Example:
- A survey can be used to gather information about a group. Often, a part of the group, called a sample, is chosen to represent the whole group or population
- A sample must represent the population fairly. In a random sample, each person in the population has an equal chance of being chosen.
- A statistic is biased if it is calculated in such a way that it is systematically different from the population parameter being estimated eg when certain individuals are being more likely to be selected than others.
- An estimator or decision rule with zero bias is called unbiased.
- Analysing information involves identifying and describing trends(patterns in data represented in tables/graphs and explain what the data indicates about the question/problem for which the data was collected.
Engage the videos below and respond to the popup questions
Video 1: Organizing Data
Video 2: Discrete and Continous data
MooMooMath & Science. (2016). Discrete and continous data (Standard YouTube licence)
Video 3: Types of data: Categorical vs numerical
365 Data Science. (2019). Types of data: Categorical vs numerical (Standard YouTube licence)