SPSS Session 2:
Hypothesis Testing and p-Values
Learning Objectives
• Review Lectures 8 and 9
• Understand and develop research hypotheses
and know difference between them and the
null hypothesis
• Define independent and dependent variables
for a research hypothesis
• Define probability and describe it’s
relationship to statistical significance
Review of Lecture 8
• Defined and discussed the theory and rules of
probability
• Calculated probability and created a
probability distribution with example data
• Described the characteristics of a normal
curve and interpreted a normal curve using
example data
Review from Lecture 9
• Defined research hypothesis, null hypothesis
and statistically significance
• Discussed the basic requirements for testing
the difference between two means
• Defined and described the difference between
the alpha value and P value, and Type I and
Type II errors
Research Hypotheses
• Hypotheses give a testable and potentially
falsifiable prediction about the relationship
between two variables.
• Designed to answer a research question of
particular interest.
• For example, in our child protection study, parent
or carer stress was predicted to be significantly
associated with the quality of the family
environment. This was a central hypothesis.
• Our research question was: Is parent or carer
stress associated with the quality of the family
environment?
Research and Null Hypotheses
• RESEARCH HYPOTHESIS
– A proposed explanation for
a phenomenon that can be
tested
– There is a relationship
between two measured
variables
– A particular intervention
makes a difference/has an
effect
NULL HYPOTHESIS
– The opposite position of
the hypothesis (usually)
– There is no relationship
between two measured
variables
– The particular intervention
does not make a
difference/has no effect
Research and Null Hypotheses Examples
RESEARCH HYPOTHESIS
• Symbolized as “H1”
NULL HYPOTHESIS
• Symbolized as “H0”
• Parent or carer stress will
be significantly
associated with the
quality of the family
environment.
• Parent or carer stress will
not be significantly
associated with the
quality of the family
environment.
Alternative Hypotheses
• Alternative or rival hypotheses may offer another explain
on why two variables may or may not be associated
• Alternative hypotheses are based on the information that
you may not have collected or didn’t consider for every
possible variable
• Other variables can:
– Be the actual cause
– Alter the relationship between the two variables
• It is important to read prior research literature before doing
your research and data collection
Independent and Dependent Variables
• Independent variables (IV) those variables of
interest which are used to predict dependent
variables (DV)
– Independent variables are also called “Predictors”.
– Dependent variables are also called “Outcomes”.
• That is IV explain variation in DV.
• For example, parent or carer stress (IV) was
predicted to be significantly associated with
the quality of the family environment (DV).
Probability
• Research and quantitative tests produce
results in probabilistic
• Probability that the association found
between an IV and DV occurred due to chance
• Can also be said that the association between
the IV and DV was statistically significant, and
therefore not due to chance
Statistical Significance
• In order to determine if something is
statistically significant, you must establish a
level of significance (represented by the Greek
letter α [alpha]).
• α = the level of probability where the null
hypothesis can be rejected with confidence
and the research hypothesis accepted with
confidence
• A common level of significance α = .05
Statistical Significance
• In statistical analyses, we find the p-value of
the association between two variables (IV and
DV).
• If the p-value is less than our α = .05 level of
significance, when we reject our null
hypothesis and accept our research
hypothesis.
• If the p-value is greater than our α = .05 level
of significance, when we say that we retain or
fail to reject our null hypothesis.