Ap Psych: In Order Observation Studies, Types of Research,Experiments, Correlation, Statisitcs

Theory:

an experiment using a intergraded set of principles that organizes observations and predicts behaviors and events ex: low self esteem feeds depression

Hypothesis

A testable prediction, often implied by a theory

Research and observations

Gathering info and recording results

Operation Definition

an experiment using a intergraded set of principles that organizes observations and predicts behaviors and events. Use number in answers. Ex; for adhd you would see how many times someone got distracted in a day

Replication

Repeating a research study with different participants and situations to see whether the basic finding can be generalized to other people

Types of Research:Descriptive Methods

Case Study and Naturalist Observation

Types of Research: Case Study

ONE PERSON is studied in depth for a long period of time in the hope of revealing universal principles ex: can a chimpanzee learn a language

Types of ResearchNaturalistic observation

Observing and recoding behavior in their natural habitat( where they usually live) without interfering/ butting in ex: what percent of their time do college students spend online?

Surveys

NOT A RESEARCH MTHOD. Questionnaires or interviews to collect data

Sample

The small group of participants out of the total number available that a research studies

Population

The total group being studied from which the sample is drawn ex: a study has some people take a pill for depression some have a placebo.. The population is the people that have depression in general

Random sampling

Everyone in the population has an equal chance of participating

Sampling Bias

A flawed sampling process that produces an unrepresentative sample

Experiments

Method of collecting data in which the research experts contact over the subjects or units in the study. Experiments applies something to someone and then measures it

Observational study ( difference with experiments)

Observes the variable not influence

Why we use experiments

To establish the cause and effect between two variables or to compare two groups on their researcg to treatments

Explanatory variable is a factor

Ex: treatment which aspirin

Explanatory varialvbe is the number answer

Ex: number of heart attacks

Examples of testing

Determine the ost effective dose of aspirin. People take the different doses( 200, 400) referred to as levels of the factor

Placebo

Thinking the treatment is working( fake medicine)

Double blind

Tester and participants don’t know the purpose of what they are doing

Blind

Subject doesn’t know the purpose

Replication

People can replicate it

Generalizability

Offer a goal of an experiment or a sample survey

Lurking variable

Variables that are hidden until the experiment happens ex: fertilizer helps plants grow( variable) but so does rain

Confounded

Can’t tell which variable is causing a effect

Two main variable so Control Group and Treatment Group

Control group receives nothing or a placebo and Treatment group receives the treatment

Hawthorne effect

People who change their behavior because they know they’re being observed

Control

Account for lurking variables so that lurking variables are in both groups

Randomization

People are randomized so it’s fair

Quasi- experiment

You follow all the rules except your sample isn’t randomized ONLY good for yo if you want to experiment on certain people or preliminary studies

Independent variable

Treatment, experimenter manipulates( changes) something related to as the treatment

Dependent variable

Result, measurable what was the outcome of the experiment. We don’t conduct the independent variable

Null hypothesis

Hypothesis that says there is no change or difference

Alter hypothesis

There is a difference or change

Significance testing

Calculation with the question “ how likely is it that my results have occurred because of change along?”

P-value

Probability that it is due to chance. Must be under .0.5 or 5% for it to be a good testing

Correlation Research/ Study

Measures relationships between 2 variables( a lot of date). THIS ISN”T ABOUT CAUSE ex: are act scores related to gpa. Is self esteem and depression related?

Correlation coefficient

Number that represents the relationship between two variables or sets of data. Note: a negative .9 has a stronger relationship than a positive .8

Only and experiment can support a hypothesis of causation. Why?

When one variable changes when adjusting another variable. Ex: people seem to be more happy when they have more shoes/ Does this mean people are more happy because they have new shoes? No. But if you run an experiment where you take away or give shoes does the happiness change?

Illusionary Correlation

The perception of a relationship where non exist. Belief that if you flip a coin multiple times the result with be random. It would be all tails, you never know.

Result variable

Is measure after the treatment

Descriptive Statistics

List and summarize data in a practical efficient way. Ex: describe characteristic of a sample

Inferential Statistics

Tell how frequently an obtained result occurred by experimental manipulation or by chance. Use details to make generalizations( Inferences) about the population

Description Statistics more info: Central Tendancy

A number that describes something about the average score of a distribution ex: mode( most frequent), median( middle), and mean( average score)

Description Statistics more info Normal Curve

A symmetrical, bell shaped curve that describes the distribution of many types of data most shared scores fall near the mean

Description Statistics more info Measures of Variance

Variability- measure of difference or spread of data. Range- how far apart the highest and lowest scores are. Standard deviation- a measure of variability that describes how much scores vary around the mean

Inferntenial Statisitics info: When is an observed difference reliable?

1. Response samples are better than biased, 2 less-variable observation are more reliable than more variable, 3 more cases are better than fewer

Inferntenial Statisitics info: Statistically Significant

The probability that a result is due to chance is smaller than .5( less than 5%. The p-value. Ask the question [ did the intervention work? Yes or no] Did it work?

Inferntenial Statisitics info: Effect size

A quantitative measurement al of the of an effect in psychological research? In simpler terms: how much of a difference was made?[ tell us how much it works] how much did is help?