Quantitative Data Collection and Analysis in Research

Posted on Nov 14, 2024 in Mathematics

Quantitative Data Collection

Development and Implementation of Surveys

Obtaining data on both objective (factual) and subjective (opinions, attitudes) aspects based on information (oral and written) provided by the subject.

Creating Questionnaires

The basic tool for data collection in survey research, producing information through questioning.

Response Bias

  • Order Effects: A tendency to always choose the first or last response alternatives (e.g., assigning a rating on a scale of 1-7).
  • Acquiescence Bias: A tendency to respond positively, regardless of the question’s content.
  • Spatial Response Bias: Preference for one response pole (e.g., always agreeing or disagreeing), regardless of content. Consider using balancing questions.
  • Social Desirability Bias: Providing socially acceptable responses to convey a positive self-image. Emphasize anonymity and that there are no right or wrong answers.
  • Positivity Bias: Tendency toward positive judgments, especially when evaluating another person. Emphasize anonymity and that there are no right or wrong answers.

Scale Development

Quantitative tools composed of a list of questions or statements that evaluate a particular construct or variable. Scales are used to assess complex constructs that cannot be measured with a single question. They consist of several items with a quantitative response format based on frequency, intensity, or degree of agreement.

Attitude Scales

Attitudes are a central theme in communication and social sciences. They are a “hypothetical” construct, not directly observable, but a latent variable inferred from measurable actions. The essence of an attitude is its evaluative nature toward a given object, providing an efficient way of evaluating the world.

Components of an Attitude

  • Cognitive: Ideas, beliefs, or opinions about an object and the information held about it.
  • Affective: Feelings and emotions evoked by the object.
  • Conative-Behavioral: Trends, provisions, or behavioral intentions toward the attitude object.

Tools to Measure Attitudes

  • Likert Scale: Assesses opinions and beliefs (e.g., strongly agree to strongly disagree).
  • Osgood Semantic Differential: Assesses the affective dimension of attitude and meaning (e.g., beautiful to ugly).

Analysis of Quantitative Data

Analyzes results from measurement tools (surveys, questionnaires, interviews, focus groups, etc.).

Descriptive Statistics

Responsible for data collection, management, and analysis from a sample.

Areas of Statistical Analysis

  • Descriptive Analysis: Describes variables by providing key characteristics (e.g., number of TVs in a home, parental education levels).
  • Inferential Analysis: Examines relationships between variables (e.g., correlation between TV viewing time and its perceived value).

Levels or Scales of Measurement

A set of numbers corresponding to each empirical mode, where each mode corresponds to a single number and vice versa.

Types of Measurement Scales

  • Nominal: Qualitative scales allowing classification and identification of objects (e.g., gender, occupation).
  • Ordinal: Qualitative scales that define objects based on criteria of greater or lesser degree, but without precise differences (e.g., finishing order in a race without a timer).
  • Interval: Quantitative scales establishing equality/inequality and order, with equal intervals between values (e.g., temperature in Celsius).
  • Ratio: Quantitative scales including an absolute zero point, indicating a total lack of a property (e.g., age, temperature in Kelvin, TV viewing time).

Key Descriptive Elements

Elements describing data, values, or scores for each variable, generally corresponding to central tendency measures, locating them within the measurement range.

  • Frequencies
  • Measures of Central Tendency
    • Mode: The most frequent value or category.
    • Median: The central value dividing the distribution in half.
    • Mean: The average of all scores.
  • Measures of Dispersion
    • Range: The spread or distance between data on the measurement scale.
    • Range (or Distance): The difference between the highest and lowest scores (XM – Xm).
    • Standard Deviation: The average deviation of scores from the mean. A larger standard deviation indicates greater heterogeneity.