Stats One Shot

• Statistics


  The science of collecting, organizing, and analyzing data
• Statistics is important for better decision making
• Data


  Facts or pieces of information that can be measured
• Descriptive statistics


  Consists of organizing and summarizing data
• Inferential statistics


  Technique of using measured data to form conclusions
• Descriptive statistics


  Calculating average, standard deviation, etc. to summarize data
• Inferential statistics


  Determining if sample data is representative of the population
• Population


  The entire group being studied
• Sample


  A subset of the population
• Sampling techniques


  • Simple random sampling
  • Stratified sampling
  • Systematic sampling
  • Cluster sampling
  • Convenience sampling
• Simple random sampling


  Every member of the population has an equal chance of being selected
• Stratified sampling


  Population is split into non-overlapping groups (strata) and samples are taken from each
• Systematic sampling


  Every nth individual from the population is selected
• Sampling techniques are chosen based on the specific scenario and requirements
• Stratified layers


  Different layers that may overlap, e.g. a PHP person may know .NET, a .NET person may know Python
• If a person is highly experienced, they may say they don't know .NET, so there will be no overlap
• Stratified sampling can be applied to different groups like doctors and engineers
• Systematic sampling


  Selecting every nth individual from the population, e.g. every 7th or 8th person for a survey
• In systematic sampling, there is no specific reason for selecting the 8th or 9th person, it is just a personal choice
• Thanos snapping his fingers may have used random sampling
• Convenient sampling


  Selecting only those people who are domain experts or interested in the specific topic of the survey
• Surveys are important to collect information and make decisions
• Exit polls would likely use random sampling
• RBI's household surveys may use stratified random sampling or convenient sampling (only surveying women)
• When testing a drug, the sampling technique depends on the target audience and use case
• Variable


  A property that can take on any value
• Types of variables


  • Quantitative
  • Qualitative/Categorical
• Quantitative variable


  Can be measured numerically and mathematical operations can be performed on them
• Qualitative/Categorical variable


  Based on characteristics, divided into categories where mathematical operations cannot be performed
• Subtypes of quantitative variables

  • Discrete
  • Continuous
• Discrete variable


  Can only take whole number values, e.g. number of bank accounts, number of children
• Continuous variable


  Can take any numerical value, e.g. height, weight, rainfall
• Examples of variable types

  • Gender (categorical)
  • Marital status (categorical)
  • River length (continuous)
  • Population of a state (discrete)
  • Song length (continuous)
  • Blood pressure (continuous)
  • Pincode (discrete)
• Types of variable measurement

  • Nominal
  • Ordinal
  • Interval
  • Ratio
• Nominal data


  Categorical or qualitative data where the order does not matter, e.g. color, gender, type of flower
• Ordinal data


  The order of the values matters but the actual values do not, e.g. student ranks based on exam scores
• Interval data


  The order and values both matter, but there is no true zero, e.g. temperature in Fahrenheit, distance
• Ratio data


  The order and values both matter, and there is a true zero, e.g. weight, height
• Frequency distribution


  A table showing the count or frequency of different categories in a data set, e.g. number of roses, lilies, sunflowers
• Frequency distribution table


  Tabulates the frequency (count) of different values or categories in a dataset