STATISTICS AND PROBABILITY

• Sampling distribution


  A graph of statistics for sample data
• Parameter


  A numerical characteristic of a population
• Statistic


  A numerical characteristic of a sample
• Sampling


  A process of selecting a subset of the population to make inferences about the population and its characteristics
• Parameter


  Data values gathered from population
• Statistic


  Data values gathered from sample
• Sampling Methods in Data Gathering

  • Surveys
  • Interviews
  • Questionnaires
• Surveys


  Most common data gathering methods, are measurements instrument consisting of a set of questions used for collecting and recording data
• Interview Types

  • Personal Interviews
  • Telephone Interviews
• Probability Sampling Methods


  • Simple Random Sampling
  • Stratified Random Sampling
  • Systematic Random Sampling
  • Cluster Random Sampling
• Simple Random Sampling


  Applicable when the population is homogeneous and all units are given equal chances to be selected as sample, uses random numbers, table of random numbers, or draw lots
• Stratified Random Sampling


  Used when the population is heterogeneous and large, the population is first divided into homogeneous groups called "strata", then a random sample of units will be selected from different stratum, commonly used when the objective is to compare the groups
• Systematic Random Sampling


  Selecting every kth term in the complete list, where k = N/n (population/sample size)
• Cluster Random Sampling


  Similar to stratified random sampling, the population is divided into subgroups called "cluster" usually along geographic boundaries, then selecting a simple random sample of cluster for which ALL the units in the selected cluster will be considered
• Non-probability Sampling Methods

  • Convenience Sampling
  • Purposive Sampling
  • Modal Instance Sampling
  • Quota Sampling
  • Expert Sampling
  • Heterogeneity Sampling
  • Snowball Sampling
• Convenience Sampling


  Also known as accidental sampling or Grab sampling, selecting a sample from the population that are easy to reach
• Purposive Sampling


  The selection of respondents is based on the purpose or objective of the study and characteristics of the population, samples are selected based on pre-determined criteria set by the researcher
• Modal Instance Sampling


  Utilized when the researcher is interested in the typicality of the units or population
• Quota Sampling


  Also known as Judgement Sampling, based on the researchers judgement
• Expert Sampling


  Sample should be drawn from the experts in the chosen topic, used when the researcher needs an expert's idea about a certain topic
• Heterogeneity Sampling


  Also known as sampling for diversity or maximum variation, used for a wide range respondents
• Snowball Sampling


  Also known as referral sampling or networking, sample are selected by recruiting acquaintances who meet the criteria of inclusion
• Types of data

  Univariate Data

  Bivariate Data

  Multivariate Data
• Univariate Data - Data that involve a single variable ony
• Bivariate Data - Data that involve two variables
• Multivariate Data - Data that involve two or more variables
• Variable - It refers to the measurables characteristics, qualities, traits or attributes of a particular individual, object, or situation being studied.