Biostat

• Sources of Data:

  • Primary Data: obtained directly from individuals, objects, or processes (e.g., questionnaires, experiment results, observation)
  • Secondary Data: obtained from another researcher or agency (e.g., books, census, Government agencies like the PSA)
• Primary Data Advantages:

  • Can be tailored to the researcher's specific needs
  • Reliable
  • Spend resources on required data only
  • Researchers' property

  Disadvantages:

  • Costly
  • Requires more time
• Secondary Data Advantages:

  • Saves time and money
  • Easy to obtain
  • Eliminates effort duplication

  Disadvantages:

  • Data may be incomplete
  • Cannot be verified for accuracy
  • Copyright restrictions
• Sampling:

  • Process of identifying who to represent from the population
  • Probability Sampling: each entity of the population has an equal chance of being part of the sample
• Probability Sampling Techniques:

  1. Random Sampling:

  • Used for very large populations
  • Each subject selected independently

  Example: Studying rice consumption pattern in Region 11
• 2. Systematic Sampling:

  • Used when the population is logically homogenous
  • Elements arranged in order and selected at regular intervals

  Example: Studying buying habits at SupermarketA
• 3. Stratified Sampling:

  • Divide the population into characteristics of importance for research
  • Divide groups into subsets

  Example: Sampling based on college graduate status
• Features to keep in mind while constructing a sample:

  1. Consistency

  2. Diversity

  3. Transparency
• Non-Probability Sampling Techniques:

  • Sample taken are non-randomized

  1. Convenience Sampling

  2. Snowball Sampling

  3. Quota Sampling
• Methods in Collecting Primary Data:

  1. Direct Method/Interview Method

  2. Indirect Method/Questionnaire Method

  3. Observational Method

  4. Experiment Method
• Data Presentation:

  • Organization of data into tables, graphs, charts, or diagrams for readability and interpretation
• 3 Ways of Presenting Data:

  1. Textual

  2. Tabular

  3. Graphs or Charts
• Types of Graphs/Charts:

  • Line Graph
  • Pie Chart/Circular Diagram
  • Bar Charts
  • Histogram
  • Frequency Polygon
• Measures of Central Tendency:

  1. Mean

  2. Median

  3. Mode
• Example Calculation:

  • Mean: 51.50
  • Median: 53.5
  • Mode: 54
• Statistics is a branch of Mathematics that deals with the collection, organization, analysis, interpretation, and presentation of data
• Descriptive Statistics:

  • Deals with the collection, organization, analysis, interpretation, and presentation of data
  • Aims to summarize data
  • Examples include daily COVID-19 positive cases in Davao City, average monthly electricity consumption, and President Rodrigo Duterte's trust rating of 94.03% according to a poll
• Inferential Statistics:

  • Deals with using probability concepts to deal with uncertainty in decision-making
  • Involves forecasting or predicting something based on gathered data
  • Examples include Singapore predicting the end of the coronavirus pandemic in December 2020 and the expected unemployment rate in the Philippines to reach 5.60% by the end of the quarter
• Population:

  • Refers to the full set of members of a certain group of interest
  • Example: students enrolled at DDC for the summer of 2020
• Sample:

  • A part or portion of the target population that represents the entire population
  • Example: female students enrolled at DDC for the summer of 2020
• Parameter:

  • A value generated from a population
  • Example: year level and course of students enrolled at DDC for the summer of 2020
• Data:

  • Refers to facts to be gathered
  • Types of data include qualitative/categorical (non-numeric data like religion, gender, and occupation) and quantitative (numerical data like age, grades, and annual salary)
• Types of Quantitative Data:

  • Discrete (integer variable) examples: number of students in a class, average grade of a student
  • Continuous (ratio variable) examples: speed of a car, water temperature