pages/Levels Of Measurement.py

import streamlit as st 
import numpy as np 
import pandas as pd 

st.title("**Level(scales) Of Measurement**")
st.header("The four scales of measurement")
st.write("By understanding the scale of the measurement we can collect and record your data")

st.subheader(":blue[**1. Nominal scale of measurement**]")
st.write("Nominal scale of measurement - You can categorize your data by labelling them in mutually exclusive groups, but there is no order between the categories.**Examples of nominal scales:** City of birth,Gender,Car brands,Marital status.")

st.subheader(":blue[**2. Ordinal scale of measurement**]")
st.write("Ordinal scale of measurement - You can categorize and rank your data in an order, but you cannot say anything about the intervals between the rankings.**Examples of ordinal scales:** Top 3 Olympic medallists,Language ability (e.g., beginner, intermediate, fluent).")

st.subheader(":blue[**3. Interval scale of measurement**]")
st.write("Interval scale of measurement - You can categorize, rank, and infer equal intervals between neighboring data points, but there is no true zero point.**Examples of interval scales:** Test scores (e.g., IQ or exams),Temperature in Fahrenheit or Celsius.")

st.subheader(":blue[**4. Ratio scale of measurement**]")
st.write("Ratio scale of measurement -  You can categorize, rank, and infer equal intervals between neighboring data points, and there is a true zero point.A true zero means there is an absence of the variable of interest. In ratio scales, zero does mean an absolute lack of the variable.**Examples of ratio scales:** Height,Age,Weight,Temperature in Kelvin")

st.image("https://static.wixstatic.com/media/63f6e6_a8f81725eb1e47bbb54fea22597a9fbc~mv2.jpg/v1/fill/w_980,h_538,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/63f6e6_a8f81725eb1e47bbb54fea22597a9fbc~mv2.jpg")