EDA-Lesson 2-3-4

• Statistics deals with the collection, presentation, analysis, and use of data to make decisions, solve problems, and design products and processes
• Descriptive Statistics (DS) involves describing the characteristics and properties of a group of persons, places, or things based on easily verifiable facts
• Inferential Statistics (IS) draws inferences about a population based on data gathered from samples using techniques of Descriptive Statistics
• Sample is a small group taken from the population, also known as a statistic
• Variables are the parameters being studied in statistics
• Qualitative Variables are non-numeric data answered with qualitative information
• Population refers to the totality of all observations from which the data set is acquired, also known as a parameter
• Discrete Data are countable quantities with finite equal intervals, like the number of individuals
• Independent Variable is a naturally occurring phenomenon that can be altered by changing its magnitude
• Dependent Variable is observed upon applying changes to the independent variable
• Controlled Variable is kept constant to check for external effects on the dependent variable
• Quantitative Variables are countable or measurable quantities
• Continuous Data are measurable quantities with infinite values between intervals, like height and weight
• Scales of Measurement:

  • Nominal: Categorical data assigned to numbers
  • Ordinal: Numbers designate the rank order of data
  • Interval: Constant range between numeric values, addition and subtraction applicable
  • Ratio: All basic mathematical operations can be performed, non-arbitrary zero point
• Sampling is the process of taking samples from the population
• Probability Sampling eliminates biases against certain events by listing all possible events and selecting them randomly

  • Simple Random Sampling
  • Systematic Sampling
  • Stratified Sampling
  • Cluster Sampling
• Non-Probability Sampling has certain or no chance of an individual being selected

  • Convenience Sampling
  • Quota Sampling
  • Purposive Sampling
• Types of Data Presentation:

  • Textual Form
  • Tabular Form
  • Graphical Form
• Univariate Analysis includes:

  • Measure of Central Tendency
  • Measure of Position
  • Measure of Variation
  • Measure of Shape
• Mean is the most widely used parameter for describing ratio data and can be arithmetic, geometric, harmonic, trimmed, or root mean square
• Median is the midpoint of values when ordered from smallest to largest, unaffected by extreme values
• Mode is the most frequently occurring value, used for nominal data and polls
• Quantiles are points taken at regular intervals from the cumulative distribution function of a random variable, including Quartiles, Deciles, and Percentiles
• Measures of Variation include Range, Mean Absolute Deviation, Variance, Standard Deviation, and Coefficient of Variation