Understanding the Difference Between Sample and Population

• Overview
• Populations are hard to observe
• Samples are less time consuming and less costly
• Lets assume we walk to university canteen to collect the details from students who will be the sample
• Sample has to have two important characteristics
  • Randomness
  • Representativeness
• Students from canteen violate both randomness and representativeness.
• In this case how to draw a sample that is both random and representative, for this we need to have an access to university student database and then we choose sample out of it which are random & reprsentative.

10000 feet overview of descriptive and inferential statistics

• Descriptive Statistics

  • 75% of the website traffic on flipkart.com is interested in mobiles
  • (We have some data & we conducted statistics on that => concluded)

• Inferential Statistics

  • According to survey which we conducted the average rent in hyderabad for 2 BHK will be 20000 by 2025
  • (This study has taken a sample and predicted the observation for the whole population)

Descriptive Statistics Fundamentals

• When we deal with statistics we deal with data
• Data is classified by
  • Types of Data
    • Categorical:
      • This represents groups or categories
      • Examples: Car Brands (BMW, Audi, Mercedes), Answer to yes/no questions
    • Numerical: This represents numbers and is divided into two categories
      • Discrete:
        • This generally represent the data that can be usually counted in a finite matter
        • Example: Number of cars, SAT score
      • Continuous:
        • This generally represents data which is not possible to count which we rather measure
        • Example: Weight, height
  • Measurement Levels
    • Qualitative
      • Nominal:
        • Represents categories that cannot be put in any order
        • Examples: Four seasons, Car brands
      • Ordinal:
        • Represents categories that cna be ordered
        • Example: rating your meal (disgusting, unappetizing, neutral, tasty and delicious)
    • Quantitative: Both represent numbers
      • intervals:
        • dont have true zeros
        • Example: Degrees celsius and Fahrenheit
      • ratios:
        • Have true zero’s
        • Example: lenght, degrees kelvin