psych chapter 2

cycle of science

cycle of science

1. theory 2) hypothesis 3) design an experiment 4) collect data 5) analyze data 6) generate conclusions

1. Theory

- General and provides predictions for multiple hypotheses

- Background information

2. Hypothesis

- Generate a questions based on understanding of theory

- make a prediction, yes/no question

- conceptual, research, statistical

3. design an experiment

- Operationalize (define) your variables in terms of specific procedures used to produce or measure it

- Design experiment to answer your question

independent variable

manipulated

dependent variable

measured- what changes

confounding variable

- cant control but will effect your dependent variable

- such as home life (conflict)

- rival explanations

participant/organism variable

- inherent to participant

- age, weight, socioeconomic status, education, relationship, gender/sex, etc.

5. Analyze Data

- Measures of central tendencies (mean, median, mode), deviation scores (statistics)

- Draw tentative conclusions

6. generate conclusions

- publish an article/peer-reviewed

- make a poster, etc.

Hindsight Understanding

- Post Hoc, after the fact

- doesn’t use scientific method

- disadvantage: bias- past events can be described in many different ways

A Priori

- understand through prediction, control and theory building

- uses scientific method, hypothesis testing, theory development

- advantages: curiosity, builds knowledge, principles can be applied to new situations

Unobtrusive Measures

- record behaviour in a way that keeps participants unaware that certain responses are being measured

- observer bias- could miss interactions which do not support testing

Descriptive method of research

- Describe the data within the sample

- Examine natural settings

- Extraneous factors not controlled- confound variables

- Low internal validity, cannot assume cause and effect

- Case studies; naturalistic observation; surveys

inferential method of research

- samples are used to generalize the entire population

correlational research

- examines relationships between two continuous variables (X and Y), then statistically measures if X and Y are related

- does not equal causation, spurious (3rd variable)

- can be used to make predictions about variables, extrapolation

- identifies real world associations

Pearson's R coefficient/ correlation

- ranges from -1.0 to +1.0

1. Direction (+) or (-)

2. Strength |value| (aka all become positive)

- Must separate strength and sign and direction

case studies

- in-depth analysis of an individual group or event

- advantages: uses for rare phenomena, challenges validity of theories, illustrate effectiveness of programs for special populations

- disadvantages: can’t determine cause-effect, does not apply to general population, researcher bias

Naturalistic observation

- observation as it occurs in a natural setting

- must be unobtrusive

- high external validity- high generalizability

- low internal validity- does not permit clear casual conclusions

hawthorne effect

- individuals change their behaviour when they know they are being watched or measured

survey research

- needs representative sample

- reflects imp characteristics of the population, but cannot study entire population

- uses random sampling- equal probability (random assignment)

- easy and cheap

- question of honest validity

bidirectional correlation

- two way causality- X causes Y, Y causes X

- Better social relationships increase happiness, optimism could attract more people and better relationships

positive correlation

- positive relationship (+), variables change in the same direction

- as height increases so does weight or shoe size

negative correlation

- negative relationship (-), variables change in opposite directions

- depression increases as number of daylight decreases

characteristics of an experiment

- manipulate the independent variable, measure the changes in the dependent variable, and control factors which might influence results

internal validity

- degree to which an experiment supports clear causal conclusions

- good experiments can be confident the independent was the cause of the dependent variable (high)

external validity

- how much experiment results can be generalized to other parts of society, settings and conditions

placebo effect

- change in behaviour based on expectations

- japanese poisonous leaf experiment

experimenter expectancy effects

- unintentional ways experimenters influence participants

- minimize w double-blind procedure or with single blind

Meta-Analysis

- A statistical procedure for combining the results of different studies that examine the same topic to test the overall significance of the findings

- Not a primary source

Cross-cultural replication

• Examining whether findings generalize across different cultures

• Theories of psychology usually have a western bias