Statistics
refers to a set of mathematical procedures for onganizing, summarizing & interpreting information
Population
the set of all the individuals of interest in a particular study
vary in size; often quite large therefore imposiisble to examine every individual in population
Sample
a set of individuals selected from a poplation, ususally intended to represent the population
Variable
a characteristic or condition that changes or has different values for different individuals
Data (plural)
measurements or observations
Data Set
a collection of measurements or observations
Datum (singular)
a single measurement or observation and is commonly called a score or raw score
Parameter
a value, usually a nuerical value, that describes a population. It is derived from measurements of individuals in a populationn
What is an example of parameter vs. statistic?
The average score of a population vs. the average score of the sample
Statistic
A value, usually numerical, that describes a sample. derived from measurements of individuals in the sample
Every population parameter has a corresponding ????
sample statistic
What are the two general categories to organize and interpret data
Descriptive and inferential statistics
Descriptive Statistics
procedures used to summarize, organize, and simplify data
Inferential Statistics
techniques that involve studying samples and making generalizations about the populations by analyzing results from the samples
Sampling Error
The discrepency or amount of error that exists between a sample statistic and a population parameter
The difference obtained in an sampling error is probaby the result of what ????
random factors of chance, not necessarily systematic differences
What must researchers have to establish the existence of a relationship?
Measurement of two variables
correlational method
measures two different variables for each individual to determine whether there is a relationship between them (ex. wake-up time & academic perfromance)
Chi-square test
used to evaluate relationships between variables for non-numerical data (ex. gender & cell phone preference)
What dont the results from a correlational study provide?
An explanation for the relationship; it only demonstrates that a relationship exist between the two variables
what are the two methods for examining relationships between two variables?
1. observe two variables as they exist naturally for a set of individuals
2. comparison of two or more groups of scores
what is the goal of an experimental study?
demonstrate a cause and effect relationship between variables
Experiemntal method
One variable is manipulated while another variable is observed and measured. Attempts to control all other variables to prevent them from influencing the results.
what are the two characteristics that differentiate experiments from other types of research studies?
Manipulation & Control
Manipulation
researcher manipulates one variable by changing its value from one level to another
Control
Researcher exercise control over situation to ensure extraneous variables do not influence the relationship being examined
what are the two general categories of varibles that researchers must consider when controlling variables?
Participant variables & Environmental variables
Participant variables
characteristics such as age, gender and intelligence. ensuure these variables dont differ from one group to another
Environmental variables
characteristics such as lighting, time of day, weather conditions. ensure these variables are the same from one group to another
When is a study considered Confounded?
when it allows more than one explanation for the results making it impossible to reach an unambiguous conclusion
what are the three techniques used to control variables?
1. random assisgnment
2. matching
3. holding them constant
Random assignment
each participant has an equal chance of being assigned to each of the treatment conditions (ex. randomly assigned to test in morning or afternoon)
Matching
ensure equivalent groups or environments (ex. assigned to groups based on similar IQ)
Holding them constant
Control variables with same characteristics (ex. use 10 yr old girls
Independent variable
the variable manipulated by the experimenter
Dependent variable
Observed variable to assess the effect of the treatment
How many variables is measured in an experiment
One
Control condition
Individuals do not receive the experimental treatment. They receive no treatment a nuetral or placebo treatment
Experimental condition
Inndividuals that receive the experimental treatement
How many values must something have before it can be called a variable?
Two
what are examples of nonexperimental methods?
1. nonequivelent groups (boys & girls-cant control which participant goes in which group)
2. pre-post studies (no control over the variables that change with time)
3. correlational studies
Nonexperimental methods
when the researcher has no ability to control the assignment of participants and cannot ensure equivalent groups- makes it impossible to use techniqus like random assignments to control partcipant variables and ensure equivalent groups
Quasi-independent variable
Independent variable in a nonexperiemntal study
Constructs
Internal attributes or characteristics that cannot be directly observed but useful in describing and explaing behavior (ex. intelligence, anxiety hunger)
Operational definition
procedures for measuring external behavior as a definition of a hypothetical construct (ex. intelliegence measured by IQ test)
Discrete variable
seperate individiable categories, restricted to whole countable numbers (ex. # of children, gender, occupation)
Continuous variable
infinite number of possible values that fall between two values. divisible into fractional parts.
real limits
boundaries of intervals for scores on a number line. (upper and lower)
Nominal scale
set of categories that have differnet names. only label and categorize. no quantitative distinctions although may be represented by numbers
Ordinal Scale
set of categories organized in an ordered sequence that rank in terms of size or magniude but do not allow you determine magnitude of difference.
Interval scale
ordered categories that are intervals of exactly the same size. The zero point is arbitrary and is a matter of reference. (ex. Fahrenheit Celsius scale)
Ratio scale
Interval scale with an absolute zero point. Ratios of numbers do not reflect ratios of magnitude.