Data Types, Population and Sampling

Data

• Data is information collected through questioning or observation.
• Data is often organized in charts or graphs, to support decisions and share information.
• Data is used to make predictions.

Types of Data

• Quantitative Data: Uses numbers. Examples include height (e.g., 5'1"), age, or temperature.
• Qualitative Data: Uses words and descriptions. Examples include eye color, favorite color, or personality traits.

Questions

• Quantitative questions collect numerical data.
• Qualitative questions collect descriptive data.

Population and Sample

• A population is the entire group of people or items studied.
• A sample is a part of the population.
• A census is when the entire population is surveyed.
• Surveys of samples are often used instead of censuses because they are less time-consuming and less expensive.

Sampling Techniques

• Simple random sampling: Randomly selecting people from the total population
• Systematic random sampling: Randomly selecting people at fixed intervals (e.g., every 5th person on a list).
• Stratified random sampling: Dividing the population into similar groups (e.g., age, gender) and randomly selecting from each group.
• Non-random sampling: Does not randomly select a sample from a population.

Data Types (Qualitative and Quantitative)

• Quantitative data: Numerical data.
  • Continuous data: Can be measured but cannot be counted (e.g., time, height, weight).
  • Discrete data: Obtained by counting (e.g., number of heads in a coin toss, number of students).
• Qualitative data: Non-numerical data (categories). Categorized by characteristics such as pet type or eye color.

Frequency Tables

• Displays frequencies of data outcomes, often with percentages to compare distributions.
• Used for populations and samples.

Data Visualizations (Stacked Bar Graphs)

• Bar graphs that show proportions of data aspects, useful to show details of large data sets.
• Showing various categories of expenses that might add up to an overall cost.

Data Analysis (Mean, Median)

• Mean: The average of a data set, calculated by summing all values and dividing by the total number of values.
• Median: The middle value in an ordered data set.
• Mode: The most frequent value in a data set.

Learn about data collection, organization, and its use in prediction. Explore quantitative and qualitative data types. Understand the difference between population, sample, census, and sampling techniques like simple random sampling.