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Hypotheses 

Getting Started 
Hypotheses are derived
from the purpose statement. A hypothesis is the researcher's prediction, derived from a theory or speculation, about how two or more measured variables will be related to each other. The two variables can be from two groups, or
comparing the group to a predetermined parameter. For example, if you
know the mean score of all students who took the SATs BEFORE this year’s
group, you can compare this year’s group to the population. 
Quantitative vs. Qualitative Research  Quantitative studies are designed to test hypotheses. Qualitative studies are often designed to develop theories and hypotheses to be tested using quantitative analysis. 
Beliefs/Predictions 
A hypothesis
is the researcher's belief about a population
parameter, or a comparison of two population parameters (e.g.,
male vs. female) 
Before Analysis 
The hypothesis must be stated before analysis. Scientific research cannot be conducted without following a set process (i.e., gathering data and then data snooping is not permitted) 
Null Hypothesis 
A hypothesis comes in a number
of different ‘flavors’: 
Alternative Hypothesis 
The alternative hypothesis states
that there is a significant difference or relationship
or that the means are NOT equal. 
Directional Hypotheses 
Alternative hypotheses MAY specify direction: The alternative hypothesis (nondirectional):
there is a significant difference The alternative hypothesis (nondirectional):
there is a significant relationship If
the statistical analysis is significant but NOT in the predicted direction,

Nondirectional Hypotheses  If the alternative hypothesis DOES NOT specify direction, then the null hypothesis is rejected regardless of the direction if the analsyis is significant. For example, if the alternative hypothesis is that men will score significantly higher than women in math, but the results indicate women are significantly higher, then the null hypothesis cannot be rejected. By contrast, if the alternative hypothesis is that there is a significant difference in math scores by genderand the results are significant, you reject the null regardless of WHICH gender's mean is higher. 
Significance Level 
Just
because two means are different does not mean they are SIGNIFICANTLY different! The significance level defines unlikely values
of a sample statistic if the null hypothesis is true 
Critical Value 
The critical value
is the dividing point between the region where the null hypothesis is
rejected and the region where it is not rejected. Read more at http://bolded.com/barrc/hyptest.pdf 
Reject/Fail to Reject 
We reject or fail to reject the null hypothesis. 
Theory
Behind 
Hypothesis testing is based on the theory
that, in a distribution of sample means, if the TRUE POPULATION MEAN is
the center point, then the odds of finding a mean too far away from that
center get less as you move to the side. 
Example 1 
Research Question: What
is the effect of a radio ad on weekly sales? 
Example 2 
Research Question: Is there a significant diference in employee job satisfaction based on type of leadership (transformational vs. transactional)
of the supervisor? 
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Copyright BOLD Educational
Software 2014
by Diane M. Dusick, Ph.D.
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