Comm 307 Study Guide

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Comm 307 Midterm Study Guide
Types of Hypotheses:
tentative statement about the relationship between IV & DV
One-tailed
predicts the specific nature of the relationship or difference
EX: Females will talk more (higher word count) than males in mixed dyadic dinner conversations Two-tailed
predicts significant relationship or difference, but does not indicate the specific nature of the relationship
EX: There is a significant difference in the quantity of words used (talkatively) by males & females in mixed dyadic dinner conversations Null (Ho)⁃
predicts that groups will not vary on DV or that there is not a relationship between 2 variables Ho: r=0
H1: r=0
H0: male talkatively = female talkatively
**you are testing the Null hypotheses

Types of Research Questions:
explicit question researchers ask about variables of interest Directional
asks if there is a positive or negative relationship or a specific difference between two or more variables
EX: Do females use significantly more words than males? Nondirectional
when researcher asks if there is no relationship between two or more variables or a significant difference occurs between two or more variables
EX: Is there a significant difference between the amount of words (talkatively) females and males? Variables:
Any entity that can take on different values
Concrete
birth order (first born, middle child, baby)
sex (male or female)
Abstract
age (a number that changes)
level of public speaking anxiety (score)
Relationships
correspondence between two variables
Correlation
Positive, Negative, No relationship
Strength and Direction
Variables:
Independent
variable(s) that is (are) manipulated or changed
we study the impact on the DV
Dependent
variables recorded or measured
we study changes in DV
**RESPONDER!
Intervening Variables
variable that intervenes between the independent variable & the dependent variable Antecedent Variables
must consider what happened previously
a study examining the impact of conflict (IV) on marital satisfaction (DV)
possible antecedent variables could potentially impact the results Variable Levels
Nominal
three rules:
mutually exclusive
equivalency
exhaustive
examples:
biological sex (male vs female)
heart attack (yes vs no)
Ordinal
three rules:
mutually exclusive
logical ordering of categories (more of something)
categorical balance
examples:
socio economic status
(lower, middle, upper)
education level
(high school, college, graduate) letter grades
(A, B, C, D, or F)
Interval
variable where the values of the categories are classified in a logical order that represents equal distances between the levels within each category
there is no absolute zero
examples:
likert scale
strongly disagree, disagree, neutral, agree, strongly agree semantic differential/bipolar adjective scale good/bad, dirty/clean, strong/weak guttman or scalogram

rarely used in comm research
to ascertain belief...
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