Readings and Overview
Topics 1 & 2
Defining concepts and specifying differences
Topic 3
Significance of problem
Topic 4
Feasibility
Topic 5
Judging quality
Topic 6
Types of hypotheses
Topic 7
Study variables
Activity #1
Topic 8
Definitions of variables
Activity #2
Week 3 Assignment
References
Feedback


Objectives 6: Differentiate between the
types of hypotheses (simple versus complex, nondirectional versus
directional, associative versus causal, and statistical versus
research). 
Research hypotheses identify the:
 Number of variables included in the study
 Type of hypothesized relationship, of which there are four categories:
 Associative versus causal hypothesized relationship
 Associative relationships involve variables that change together. Associative relationships are also directional or nondirectional. For example:
 X is related to (r/t) Y and Z  predicts a relationship
 As X increases, Y increases  predicts a positive relationship (because they vary in the same direction)
 As X decreases, Y decreases  predicts a positive relationship (because they vary in the same direction)

As X increases, Y decreases, or as X decreases, Y increases  predicts
a negative relationship (because they vary in the opposite directions)
 Causal relationships predict that one variable, the independent variable, causes another variable, which is the dependent variable.
 The independent variable, also called the treatment or experimental variable, is manipulated by the researcher to cause an effect on the dependent variable
 The dependent variable, also called the outcome or criterion variable, is measured before and after manipulation of the independent variable to estimate the effect of the independent variable.

Example  Compared to nonparticipants, subjects participating in a
program of meditation (independent variable) will report less perceived
stress (dependent variable).
 Simple versus complex hypothesized relationship 
 A simple hypothesis states the relationship (associative versus causal) between two variables, the independent variable and the dependent variable.
 A complex hypothesis predicts the relationship between three or more variables. The variables may include:
 A single independent variable and two or more dependent variables.
 Example  Compared to nonparticipants, subjects participating in a program of meditation (independent variable) will report less perceived stress (a dependent variable) and will have lower blood pressure readings (a dependent variable)
 Two or more independent variables and one, or more, dependent variable(s).

Example Compared to nonparticipants, subjects participating in a
program of meditation and/or a program of regular physical activity
(two independent variables) will report less perceived stress (a dependent variable) and will have lower blood pressure readings (a dependent variable).
 Directional versus nondirectional hypothesized relationship 
 A directional hypothesis is also an associative hypothesis, and states the direction of the predicted relationship
 Positive
 As X increases, Y increases
 As X decreases, Y decreases
 Negative
 As X increases, Y decreases
 As X decreases, Y increases
 A nondirectional hypothesis predicts that there will be a relationship, but this type hypothesis does not predict the direction.
 All causal hypotheses
predict the direction of the relationship. The direction is usually
apparent by the use of terms such as less, more, increase, decrease,
greater, higher, lower, etc.
 An example Compared to nonparticipants, subjects
participating in a program of meditation, twice a week or four times a
week (two independent variables  twice a week meditation or four times a week) will report less perceived stress (a dependent variable) and will have lower blood pressure readings (a dependent variable).
 Null versus research hypothesis
 The null hypothesis (Ho) is also called the statistical hypothesis.
 It states that there is no relationship between variables.
 It is used for statistical testing and interpreting the results of statistical analyses.
 It can be simple or complex and associative or causal.
 It may not always be stated, but it is implied, because it is the opposite of the research hypothesis.
 An example  There is no difference in measures of perceived stress (a dependent variable) and blood pressure (a dependent variable) between subjects who do and do not participate in a program of meditation (independent variable).
 The research hypothesis (HA or H1) is also called the alternative hypothesis, since it is the opposite of the null hypothesis.
 It states that there is a relationship between variables.
 It can be simple or complex, associative or causal, and directional or nondirectional.
 There are several examples of research hypotheses in the preceding illustrations.
