CH. 2 DEFINITIONS [UNIT 1]

Central tendency of a set of data

Mean, median, and mode

Mean

Average

Median

50th percentile, the middle value when the set is ordered

Mode

Most common value

Range

Max value - min value

Standard deviation

Measure of the deviation/difference of the individual data values from the mean of those values

Normal curve

Symmetric bell-shaped distribution (i.e. mean = mode = median) where about 68% of scores fall within one standard deviation of the mean

P-value

Probability of the data assuming that there are no differences between the two groups

What affects the p-value?

Effect size, variability of the data, sample size

Independent variable

Causes changes in something else (dependent variable)

Difference between independent + dependent variables

What is the experimenter manipulating and measuring?

Descriptive

Allows us to summarize collected data

Inferential

Allows us to make inferences about the larger population based on the results from our smaller sample

Basic Research

Answers fundamental questions about behaviour (Ex. Biopsychologists study how nerves conduct impulses from skin receptors)

Applied Research

Investigates issues that have implications for everyday life + provides solutions to everyday problems

Empirical

Based on a systematic collection + analysis of data

Scientific method

1. Develop General Theories

2. Make Observations

3. Think of Interesting Questions

4. Formulate hypotheses

5. Develop Testable predictions

6. Gather Data to test predictions

7. Refine, alter, expand, or reject hypotheses

Laws

Principles that are so general + applicable to all situations in a given domain of inquiry

Stage Theory of Cognitive Development (Swiss Psychologist Jean Piaget 1952)

Children pass through a series of cognitive stages as they grow, mastering in succession before movement to the next cognitive stage can occur

Hypothesis

General statement about relationships between variables

Operational

Refers to the measurement properties of a variable, shows exactly what’s being measured

Research Design

Specific method a researcher uses to collect, analyze, and interpret data

Descriptive Research

Designed to provide a snapshot of the current state of affairs

Correlational Research

Assess the relationships between and among two or more variables

Experimental Researc

Assess the causal impact of one or more experimental manipulations on a dependent variable (cause + effect)

Sample

The people chosen to participate in the research

Representative Sample

Age, sex, gender orientation, socioeconomic status ethnicity, etc…

Generalizability

Won’t apply well to anyone who wasn’t represented in the sample

Archival Research

Data that’s been previously collected

Psychological Tests

Measures developed by psychologists to assess ones’ score on a psychological construct (Ex. extroversion, self-esteem, aptitude for a particular career)

Validity

Exists when a measured instrument actually measures what you think it’s measures

Reliable

Exists when a test/survey give the same responses time to time or in different situations

WEIRD bias

Western, educated, industrialized, rich, and democratic

Naturalistic Observation

Research based on the observation of everyday events

Correlation coefficient

Can be either + or -, ranging in value from -1.0 through 0 to 1.0

Pearson Correlation Coefficient ( r )

The closer the coefficient is to -1 or +1, and the further away from zero, the greater the size of the association between the two variables (Ex. r =-.54 is stronger than r = .30)

Scatterplot

Visual image of the relationship between two variables

Third Variable

Not part of the research hypothesis but causes both observed variables to correlate

Independent Variable

Manipulated by the researchers so that there’s more than one condition

Dependent Variable

Outcome/score on the measure of interest that is dependent on the actions of the independent variable

Experimental Manipulation

Occurs prior to the measured dependent variable

Initial Equivalence

Using random assignments to conditions

Descriptive Statistics

1st step in understanding how to interpret the data you collected

Normal Distribution

Data distribution that is shaped like a bell

Arithmetic Mean ( M )

Most commonly used measure of central tendency; computed by calculating the sum of all of the scores of the variable and dividing this sum by the number of participants in the distribution, denoted by the letter N

Dispersion

Refers to the extent to which the scores are al tightly clustered around the central tendency

Standard deviation ( S )

Most commonly used measure of variability around the mean

Inferential Statistics

Provides researchers with the tools to make inferences about the meaning of results

P values

Used to determine whether or not effected detected in the research are present

Protection from harm

Participants’ physical + mental wellbeing must be protected

Use of Deception Minimized

Researchers must balance the use of deception, (Ex. not disclosing the true purpose of the study, with potential harm to the participants)

Debrief Participants

Participants must be fully informed about the purpose of the research and their participation

Care for vulnerable participants

Researchers must respect childrens’ rights + other vulnerable population to participate in research and to have the above requirements safeguareded by an advocate (Ex. a parent)

Confounding variable

Something that varies together your independent variable and you’re not controlling for it