Data Analysis

• Descriptive statistics

• Inferential statistics

• Significance

• Bar graph

• Histogram

Descriptive Statistics: Summarizing and describing data e.g. calculating mean, median, and mode

Inferential Statistics: Making predictions or inferences about a population based on a sample, e.g hypothesis testing.

Significance: Statistical significance indicates whether an observed effect is likely due to chance.

Bar Graph:  Bar graphs display categorical data 

Histogram: histograms show the distribution of continuous data

Describing a Study

• Aim

• Procedure

• Results

• Findings

• Implications

Aim: The purpose of the study.

Procedure: Detailed steps followed in the study.

Results: Presentation of collected data.

Findings: Interpretation of results.

Implications: The broader significance or applications of the study.

Ethics

• Anonymity

• Informed consent

• Debriefing

• Undue stress or harm

Anonymity: Ensuring participants' identities are not disclosed.

Informed Consent: Participants are fully aware of the study and agree to participate.

Debriefing: Providing participants with information after the study is complete.

Undue Stress or Harm: Avoiding unnecessary psychological or physical harm to participants.

Experimental Design

• Lab

• Field

• Quasi

• Natural Experiments

Lab Experiment: Lab experiments are conducted in a controlled environment, often a laboratory, where researchers can manipulate variables and control extraneous factors to isolate the effects of the independent variable. e.g. Suppose you want to study the effects of caffeine on memory. You could conduct a lab experiment by having participants consume different amounts of caffeine and then testing their memory using standardized tasks in a controlled lab setting.

Field Experiment: Field experiments take place in real world settings, outside of the controlled environment of a laboratory. Researchers manipulate variables, but the conditions are less controlled compared to lab experiments. e.g. If you're interested in studying the impact of advertising on consumer behavior, you might conduct a field experiment by manipulating the placement or content of advertisements in a real shopping mall and observing the resulting changes in consumer behavior.

Quasi Experiment: Quasi experiments share similarities with true experiments, but they lack full randomization of participants to experimental and control groups. This could be due to ethical concerns, logistical challenges, or other practical constraints. e.g. Imagine you want to investigate the impact of a new teaching method on student performance. Instead of randomly assigning students to different teaching methods (which might be impractical or ethically challenging), you could compare the performance of students in classes where the new method is implemented versus classes where the traditional method is used.

Natural Experiment:Natural experiments occur when the researcher takes advantage of naturally occurring situations where random assignment is not feasible, but conditions resemble a true experiment. e.g. Consider studying the impact of a sudden policy change on air quality. If a city introduces a new environmental regulation, you can compare air quality data before and after the policy change to assess its impact. In this case, the researcher didn't manipulate the variable but utilized a naturally occurring event.

Null Hypothesis: Null hypothesis assumes no effect

Research hypothesis: research hypothesis predicts an effect.

Random Allocation: Randomly assigning participants to different experimental conditions.

Independent Samples: Participants are only in one experimental condition.

Repeated Measures: Participants experience all experimental conditions.

Evaluating Research

• Demand characteristics

• Social desirability effect

• Ecological validity

Demand Characteristics: Participants alter their behavior based on perceived expectations.

Social Desirability Effect: Participants respond in a way they believe is socially acceptable.

Ecological Validity: The extent to which study conditions reflect real world situations.

Non Experimental Methods

• Observations 

• Case studies

• Method triangulation

Observations: Systematic watching and recording of behavior.

Case Studies: In Depth analysis of an individual, group, or event.

Method Triangulation: Using multiple research methods to study the same phenomenon.

Sampling

• Opportunity 

• Random

• Snowball

• Self selected

• Stratified

• Representative 

Opportunity Sample: Participants chosen based on availability.

Random Sample: Every member of the population has an equal chance of being selected.

Snowball Sample: Participants recruit others for the study.

Self Selected Sample: Participants volunteer to take part.

Stratified Sample: Ensures representation of subgroups.

Representative Sample: Reflects the characteristics of the population.

Types of Data

• Anecdotal data

• Empirical data

Anecdotal Data: Personal stories or experiences.

Empirical Data: Collected through systematic observation or experimentation.

Validity vs. Reliability

• Internal

• construct

Internal Validity: The degree to which an experiment accurately measures what it intends to.

Construct Validity: The extent to which a test measures the construct it claims to measure.

Variables

• Independent

• Dependent

• Controls

• Placebos

• Operationalization 

Independent variable: Independent variable is manipulated

Dependent variable: dependent variable is measured.

Controls: Factors kept constant to prevent confounding.

Placebos: Inactive substances or treatments.

Operationalization: Defining variables in measurable terms.