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Probability » Binomial Distribution » Normal Distribution » Regression » Statistics and Probability

Discrete vs. Continuous Data

Discrete Data

Discrete data can only take specific, distinct values (often integers). It's typically counted. There are no intermediate values possible between two consecutive discrete values.

Examples: Number of students in a class, number of cars in a parking lot, shoe sizes (e.g., 7, 7.5, 8, but not 7.23), results of a dice roll.

Continuous Data

Continuous data can take any value within a given range. It's typically measured. Infinitely many values are possible between any two continuous values.

Examples: Height of a person, temperature, time taken to complete a task, weight of an object.

Understanding the type of data is crucial as it often dictates the appropriate methods for analysis and presentation.

Pictograms

Pictogram Generator

Data (Category:Value, one per line, e.g., Apples:30):

Symbol (Emoji or char):

Value per Symbol:

Bar Charts

Bar Chart Generator

Data (Category:Value, one per line):

Chart Type:

Percentage Component Bar Charts

Percentage Component Bar Chart Generator

Data (Category;Component1:Value1,Component2:Value2;... one category per line): Example: Group1;CompA:10,CompB:20 (new line) Group2;CompA:15,CompC:25

Pie Diagrams (Pie Charts)

Pie Diagram Generator

Data (Category:Value, one per line):

Tally Diagrams & Frequency Distributions

Tally & Frequency Distribution Generator

Raw Data (comma-separated values, e.g., 1,2,2,3,1,4,2,5):

Histograms

Histogram Generator

Frequency Data (ClassStart-ClassEnd:Frequency, one per line): Ensure class intervals are continuous (e.g., 0-10, 10-20).

Statistics & Data Calculator