Data collection and representation

Data collection and representation

Data Collection

  • Primary data is raw data that is collected directly by the individual or group conducting the research. Surveys, observations, and experiments are all ways of gathering primary data.

  • Secondary data is data that has already been collected and analysed by someone else. It can come from a variety of sources, such as books, newspapers, and governmental reports.

  • Random sampling can be used to minimize bias in data collection. It ensures that each member of the population has an equal chance of being selected.

  • Sampling methods such as stratified, systematic, quota, and opportunity sampling may be used based upon the nature of the study and its objectives.

  • It’s important to consider the reliability and validity of the data collected. This can be influenced by the method of data collection and the sample size used.

Data Representation

  • Data can be represented in various forms like graphs, charts, tables, and diagrams.

  • Histograms are used to display continuous data. They are similar to bar charts but the bars touch each other which represents that there are no gaps between data.

  • Pie charts are used to represent categorical data. Each segment of the pie represents a particular category, and the size of the segment is proportional to the frequency of that category.

  • Bar charts are useful for comparing data across categories. Each bar represents a category, and the height of the bar represents the frequency.

  • Scatter plots represent two-variable data. Each point on the plot represents an individual data point.

  • Box-and-whisker plots or box plots provide a way to represent a data set using five statistical figures: minimum, first quartile, median, third quartile, and maximum.

  • Stem-and-leaf displays offer a quick and easy way to organise data while still preserving the individual data values.

  • Data representation can be useful for understanding the spread and skewness of data. These will be visual and immediate in the plots.

  • Remember to use appropriate scales and correctly label axes when representing data.