1._Stats_Intro

Chapter 1: Introduction to Statistics

• Definition of Statistics

  • Statistics is a collection of methods for collecting, displaying, analyzing, and drawing conclusions from data.

  • Methods must be followed sequentially (systematized process): collect, display, analyze, draw conclusions.

• Steps in Statistics

  1. Collecting Data

     • Data collection is the first step, essential for research.

  2. Displaying Data

     • Displaying data involves tallying the data from respondents or questionnaires, e.g., using Google Forms.

  3. Analyzing Data

     • Analyze the tallied data before drawing conclusions.

  4. Drawing Conclusions

     • Conclusions can only be made after thorough analysis.

• Types of Statistics

  • Descriptive Statistics

    • Organizes, displays, and describes data.

    • Example: Describing a phone’s attributes—color, size, features.

  • Inferential Statistics

    • Based on sample data from a larger population to make inferences about that population.

Chapter 2: Types of Data

• Definition of Data

  • Data is the information collected for research.

• Types of Data

  • Qualitative Data

    • Measures characteristics without a numerical scale, focusing on attributes and labels.

    • Example: Describing a phone as lightweight or having many applications.

  • Quantitative Data

    • Involves numerical values and measurements.

    • Example: A phone with 128 GB of storage.

Chapter 3: Qualitative and Quantitative Research

• Qualitative Research

  • Focuses on gathering non-numerical data, typically through interviews.

  • Example: Researching the effects of martial law through personal accounts.

• Quantitative Research

  • Gathers numerical data, often through questionnaires.

  • Example: Using Likert scale for responses (strongly agree to strongly disagree).

• Combining Qualitative and Quantitative Research

  • While they are distinct, both can be used in conjunction to enrich research analysis and findings.

Chapter 4: Population vs. Sample

• Definition of Population

  • The entire group being studied.

• Definition of Sample

  • A subset of the population selected for analysis.

  • Using samples represents the population without surveying every individual.

• Importance of Sampling

  • To produce reliable research results without needing to survey the complete population.

Chapter 5: Using the Formula for Sampling

• Reliability in Sampling

  • Using Slovin's formula to determine the sample size ensures reliable results.

  • Slovin's Formula:[ n = \frac{N}{1 + N \cdot e^2} ]

    • n = sample size

    • N = population size

    • e = margin of error (commonly between 0.08 and 0.12).

• Statistical Validity

  • Samples must be determined based on factual statistics rather than assumptions.

Chapter 6: Probability

• Definition of Probability

  • Probability indicates the likelihood of an event occurring, ranging from 0 (impossible) to 1 (certain).

• Probability Scale

  • 0% to 49% indicates low probability; 51% to 100% indicates high probability.

• Types of Probability

  • Unconditional Probability

    • No conditions need to be met for the event to occur.

    • Example: Receiving a gift without any prerequisites.

  • Conditional Probability

    • Depends on the occurrence of a prior event.

    • Example: "I will give you a reward if your average score is 80 or higher."

• Application of Probability

  • Used in various fields, such as weather forecasting and assessing election outcomes.