Levels
🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟🪟
- Four measurement scales - ways to categorize different types of variables and choose the right statistical test, visualization technique, and guide data analysis.
- nominal - names/ labels
- ordinal - order is important
- interval - space between/ tell us about order and the value between each item
- ratio - ultimate order, interval values, plus the ability to calculate ratios since a true zero can be defined
Qualitative Data 🟥🟥🟥🟥🟥🟥🟥🟥
- Nominal Variables - values are not ordered like nationality, gender, etc.
- Nominal scales are used for labeling variables without any quantitative value.
- They could simply be called labels
- nominal sounds like names and these scales are like names or labels.
- At this level, you can not do any quantitative mathematical operations like addition or division.
- You can do basic counts using pandas' value _counts method
- graphs like bar charts, and pie charts.
- Ordinal Variables -
- the order of the values is important and significant but the differences between each one are not known.
- typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.
- Ordinal sounds like order and it is the order that matters and that is all you really get.
- We can do basic counts as we do with nominal data and have comparisons and orderings.
- graphs like bar and pie charts but now we can calculate medians and percentiles
- with medians and percentiles stem and leaf plots as well as box plots are possible.
Quantitative Data🟦🟦🟦🟦🟦🟦🟦🟦🟦
- Two types of Quantitative variables
- Discrete Variables - their values are countable and can only assume certain values with no intermediate values like the number of heads in 10 coin tosses
- Continuous Variables - can assume any numerical value over a certain interval or intervals example the height of a person.
Interval
- numeric scales where we know both the order and the exact differences between the values.
- Celsius temperature is an example because the difference between each value is the same.
- The histogram - visualizes buckets of quantities and shows the frequencies of these buckets and we can use scatter plots - where we can graph two columns of data on our axes and visualize data points as literal points on the graph.
- Don't have a true zero - there is no such thing as no temperature. Negative numbers also have a meaning.
- We can add and subtract but can not multiply or divide.
Ratio
- tell us about order, exact value between units, and have an absolute zero.
- height and weight are examples of this.
- They can be added, subtracted, multiplied, and divided.
- Central tendency can be measured by mode, median, or mean
- Measures of dispersion such as standard deviation and coefficient variation can be calculated from ratio scales.
- Discrete Variables - their values are countable and can only assume certain values with no intermediate values like the number of heads in 10 coin tosses
- Continuous Variables - can assume any numerical value over a certain interval or intervals example the height of a person.
- numeric scales where we know both the order and the exact differences between the values.
- Celsius temperature is an example because the difference between each value is the same.
- The histogram - visualizes buckets of quantities and shows the frequencies of these buckets and we can use scatter plots - where we can graph two columns of data on our axes and visualize data points as literal points on the graph.
- Don't have a true zero - there is no such thing as no temperature. Negative numbers also have a meaning.
- We can add and subtract but can not multiply or divide.
- tell us about order, exact value between units, and have an absolute zero.
- height and weight are examples of this.
- They can be added, subtracted, multiplied, and divided.
- Central tendency can be measured by mode, median, or mean
- Measures of dispersion such as standard deviation and coefficient variation can be calculated from ratio scales.
🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️🌡️
References
https://medium.com/@rndayala/data-levels-of-measurement-4af33d9ab51a
No comments:
Post a Comment