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Task #Experiential Learning
Create a list of variables related to your classmates, such as height, eye colour, hair length and weight. Ensure
your list covers nominal, ordinal, interval, or ratio level variables. Define clear response categories that are
exhaustive and mutually exclusive. For instance, for eye colour, categories could include blue, brown, green,
hazel, and other.
Reboot
Indicate whether the variable is ordinal or not. Write the variable type, if it is not ordinal.
1. Are you eligible to vote?
2. How did you like the session? (1-5)
3. Heights of men (in inches).
4. Grading in exams (A,B,C,D).
Statistical Analysis of Data
Mean
Statistical analysis involves collecting, exploring, and
presenting large datasets to identify patterns and trends.
It is a powerful tool that employs statistical, tests and Measures of Central Median
methodologies to derive meaningful conclusions from raw Tendency
data. It helps in predicting future trends and making informed
decisions based on historical patterns. Mode
Calculating Measure of Central Tendency using Python
Statistical analysis can be performed using the Python programming language. That requires us to import the library
statistics into the Python program. Some significant functions that we will utilise in future programs in this module
include:
Function Description
statistics.mean() Calculates the mean (average) of the provided data.
statistics.median() Calculates the median (middle value) of the provided data, when arranged in order.
statistics.mode() Determines the mode of provided numerical or nominal data.
statistics.stdev() Computes the standard deviation from a sample of data.
statistics.variance() Calculates the variance of a sample of data.
Data Literacy—Data Collection to Data Analysis 283

