Research Methods: A Comprehensive Study
Side 1: Chapter 4 – Research Design
Definition
The plan or blueprint for a study, outlining how data will be collected and analyzed.
Types
- Exploratory
- Descriptive
- Causal
Key Research Design Types
Exploratory Research
Conducted when little is known, aims to gain insights and clarify ideas.
Descriptive Research
Provides a detailed description of phenomena, without manipulation.
Causal Research
Establishes cause-and-effect relationships between variables.
Sampling Design
Probability Sampling
Every member of the population has a known chance of being selected (e.g., simple random sampling).
Nonprobability Sampling
Not every member has a chance of being selected (e.g., convenience sampling).
Data Collection Methods
Qualitative
Observations, interviews, focus groups.
Quantitative
Surveys, experiments, numerical data.
Sampling Errors and Biases
Sampling Error
Differences between sample and population due to random chance.
Systematic Error
Bias in data collection or sampling procedures (e.g., selection bias).
Chapter 5 – Hypothesis Testing
Hypothesis
A testable statement about the relationship between two or more variables.
Types
- Null Hypothesis (H₀): Assumes no effect or relationship.
- Alternative Hypothesis (H₁): Assumes there is an effect or relationship.
Steps
- Formulate null and alternative hypotheses.
- Select significance level (α), typically 0.05.
- Collect data and compute test statistic.
- Compare test statistic to critical value to reject or fail to reject H₀.
Types of Errors
Type I Error
Rejecting the null hypothesis when it is actually true (false positive).
Type II Error
Failing to reject the null hypothesis when it is actually false (false negative).
P-value
The probability of observing data at least as extreme as the sample data, given that the null hypothesis is true.
If p < α, reject the null hypothesis.
Chapter 6 – Reliability and Validity
Reliability
Consistency of a measurement over time.
Types
- Test-retest reliability
- Inter-rater reliability
- Internal consistency
Validity
The extent to which a measurement actually measures what it is intended to measure.
Types
- Content Validity: Ensures the measure covers all relevant aspects.
- Criterion Validity: Measures how well one measure predicts an outcome.
- Construct Validity: Assesses if the test measures the intended construct.
- Face Validity: The degree to which a measure appears valid on the surface.
Improving Reliability and Validity
- Use clear, consistent operational definitions.
- Pilot testing and revising measures based on feedback.
Chapter 7 – Experimental Research Design
Experimental Research
Involves manipulation of variables to observe causal effects.
Key Elements
- Independent variable (IV)
- Dependent variable (DV)
- Random assignment
Types
True Experimental Design
Randomly assigns participants to treatment/control groups.
Quasi-Experimental Design
Lacks random assignment, but controls other variables.
Control Group
A group not exposed to the independent variable, used for comparison.
Internal and External Validity
Internal Validity
The extent to which the experiment accurately measures the relationship between IV and DV.
External Validity
The generalizability of the study results to other settings or populations.
Side 2: Chapter 9 – Survey Research
Survey Research
A method of gathering data by asking questions to a sample of people.
Advantages
- Cost-effective
- Large sample size
- Versatile in measuring various variables (attitudes, behaviors)
Types
Descriptive
Used to describe characteristics or behaviors.
Analytical
Used to test hypotheses or analyze relationships between variables.
Data Collection Methods
Self-Administered
Online surveys, mail surveys.
Interviewer-Administered
Phone surveys, face-to-face interviews.
Sampling Methods
Probability Sampling
Random sampling, stratified sampling.
Nonprobability Sampling
Convenience sampling, judgmental sampling.
Survey Design
Question Types
- Open-ended
- Close-ended
- Likert scale
Avoiding Bias
Be clear, neutral, and specific with wording.
Common Survey Issues
Nonresponse Bias
When certain groups fail to respond.
Response Bias
When answers are influenced by question wording or social desirability.
Chapter 13 – Measurement
Concepts and Variables
Concepts
Abstract ideas (e.g., intelligence, happiness).
Variables
Quantifiable characteristics (e.g., age, income).
Levels of Measurement
Nominal
Categories with no order (e.g., gender, race).
Ordinal
Ordered categories (e.g., rankings).
Interval
Ordered, equidistant categories without a true zero (e.g., temperature).
Ratio
True zero point, ordered, and equidistant (e.g., weight, height).
Reliability and Validity
Measurement consistency (reliability) and accuracy (validity).
Factor Analysis
A statistical method used to identify underlying variables (factors) that explain correlations among measured variables.
Chapter 15 – Questionnaire Design
Importance
A well-designed questionnaire ensures reliable, valid, and actionable data.
Question Types
Open-Ended
Allows for free-response.
Closed-Ended
Respondents choose from pre-set options.
Writing Effective Questions
- Clear and Specific: Avoid ambiguity.
- Avoid Bias: Don’t lead the respondent toward a particular answer.
- Simple Language: Ensure respondents can understand the question.
Question Sequence
- Start with easy, non-sensitive questions.
- Use filter questions to guide respondents to relevant sections.
Pretesting
Pilot test the questionnaire to identify any issues before data collection.
Survey Administration
- Decide on the mode (online, mail, in-person) based on target audience.
- Ensure proper training for survey administrators to reduce bias.