Update app.py

app.py

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 import streamlit as st
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-st.title("Statistics:The Pathway for Data Analysis")
-st.header("What is Statistics")
-st.write("Statistics is the science of analysing data.")
-st.write("Statistics involve analysing data , interpreting data and processing it into meaningful insights which are used further to build a model.")
-st.header("Types of Statistics")
-st.write("The data we collect will decide which type of statistics we must use.")
-st.write("The data we collect may be of two types namely, Population and Sample.")
-st.subheader("Population")
-st.write("For the problem statement, if we find each and every observation and whole data is involved then it is Population")
-st.markdown("**Example**")
-st.write("consider a family of 10 members . If we have to find how many are non veg lovers, we can ask each and every person of the family and can know it.")
-st.write("In the above example we consider opinion of every person in the family and come to the conclusion about how many love non-veg. So we take in every observation to provide desired result. This is Population.")
-st.write("It is practically impossible to find population of large datasets , that is why Sample came into play.")
-st.write("When we measure the population then its :blue[_Parameter_]")
-st.subheader("Sample")
-st.write("For the problem statement, if we find observations for only some observations which represent the whole data, then it is Sample. ")
-st.markdown("**Example**")
-st.write("consider If we have to find how many are non veg lovers present all over the world.")
-st.write("In the above example, It is not possible to enquire each and every person around the world to know their preferences.Instead , we can enquire some people from each country as a survey and consider those responses to find the desired results. This is Sample.")
-st.write("When we measure the Sample  then its :blue[_Statistics_]")
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-st.markdown("***There are two types of Statistics namely, Descriptive and Inferential statistics***")
-st.subheader("Inferential Statistics")
-st.write(" This method is used to describe about whole population based on the sample we have.")
-st.subheader("Descriptive Statistics")
-st.write("This method is maily used to summarise or describe you collected data with different types of measures")
-st.write("We can use descriptive statistics even when we have sample as well as population.")
-multi='''The descriptive statistics is majorily divided into 3 types -
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-1.Measures of Central tendency 
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-2.Measures of Dispersion / Variability 
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-3.Distribution'''
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-st.markdown(multi)
-st.subheader("Measures of Central Tendency")
-st.write("These are the measures that finds the central or average value of Data.")
-st.write("These mainly include Mean , Median and mode")
-st.markdown("**MODE**")
-st.write("Mode mainly states about the occurences of particular value.")
-st.write("Mode is of many types like, 0 modes,uni mode Bi-mode, Tri-modes and multi-modes.")
-st.write("**The main disadvantage of mode is**")
-st.write("Due to its dependency on frequency , sometimes we can calculate mode and sometimes we cannot.")
-st.markdown("**MEDIAN**")
-st.write("""Median is mainly used to give precise central value
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-This process maily consists of sorting the data and then finding the central value.""")
-st.write("**The main disadvantage of median is**")
-st.write("Its complete concentration will be on the central value and sorting takes time")
-st.markdown("***Both median and mode will not consider all the observations so we wont opt to these measure mostly.***" )
-st.markdown("**MEAN**")
-st.write("Mean is the average value of our whole dataset. It is the mostly used measure to find the central tendency.")
-st.write("Mean can be given by ratio of sum of all observations and total number of observations")
-st.write("""Mean is of 3 types :
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-1.Arithematic mean
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-2.Geometric mean
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-3.Harmonic mean""")
-st.subheader("Measures of Dispersion/Variablity")
-st.write("These are the measures to find how our data is spread or organised around the central value.")
-st.write("Measures of Dispersion are of two types namely, Absolute and Relative")
-st.subheader("Absolute")
-st.write("Absolute value is a single value that describes the spread. This has units.")
-st.write('''Absolute measures are further divided into:
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-**Range** : we use range when we are given with minimum and maximum values.
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-**Quartile Deviation** : we use this when a list is given and we must split them with equal intervals.
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-**Variance** : we use this when we need to find the spread using mean.
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-**Standard Deviation** : It is the root value of variance, this is the most used measure as it gives accurate spread.''')
-st.subheader("Relative")
-st.write("Relative measure  is used when we have different type of data and we need to find its relation. This doesnot have units.")
-st.write('''Relative measures are further divided into:
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-**Coefficient of Range** 
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-**Coefficient of Quartile Deviation**
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-**Coefficient of Variance** : We use this in most of times, its main function is to know about the consistency in data.When data has high variance it has less consistency
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-**Coefficient of Standard Deviation** ''')
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+st.title("WELCOME TO DATA ANAYSIS...!!")
+st.image("
+
+![Uploading image.png…]()
+
+, caption="DATA ANALYSIS")
+st.write("Embark your journey with us to honour the progress in Data Analysis.")
+st.subheader("What is Data Analysis")
+st.write("Data analysis is the process of examining, cleaning, transforming, and interpreting data to find insights, patterns, and make informed decisions.")
+st,subheader("What we learn Here:")
+st.write("1.Basics of Data Analysis")
+st.write("2.How Statistics are used to analyze data.")
+st.write("3.What are the different types in data used for performing statistics.")
+st.write("4.Levels of Measurements")
+st.write("5.Descriptive Stastistics")