Research hypothesis
The research hypothesis states that there is an association or difference
With hypothesis testing, the research hypothesis states that there IS a difference or association between variables of interest. Researchers have conducted a literature review and created a valid and credible research question. Now, they can make an informed and evidence-based research hypothesis that there will be a difference/association/effect.
When statistical significance is achieved in the context of hypothesis testing, then researchers "reject" the null hypothesis. This means that researchers have found a significant difference/association/effect, and can therefore reject the idea that there is NO difference/association/effect.
When conducting research, this is the researchers' hypothesis. They are unsure if a treatment or a characteristic or a predictor/independent variable has an association with an outcome/dependent variable, but they believe it does. They are conducting the research study to see if it does or does not exist. The research hypothesis is the reason for conducting research. There is a research question that needs to be answered, and researchers believe that what they want to do or study is an answer to that question!
Remember that human beings bring presuppositions and biases into everything they do. This is especially true in applied research and hypothesis testing. It just feels GOOD to find the outcomes/differences/associations that researchers believe exist. And researchers will cut corners and manipulate their data analyses in order to find truth in their hypotheses. This is a good reason for the focus of hypothesis testing being strictly on the null hypothesis. When statistical significance is not achieved when testing the primary hypothesis (p > .05), then it is the null hypothesis that researchers "do not reject," rather than the research hypothesis.
When statistical significance is achieved in the context of hypothesis testing, then researchers "reject" the null hypothesis. This means that researchers have found a significant difference/association/effect, and can therefore reject the idea that there is NO difference/association/effect.
When conducting research, this is the researchers' hypothesis. They are unsure if a treatment or a characteristic or a predictor/independent variable has an association with an outcome/dependent variable, but they believe it does. They are conducting the research study to see if it does or does not exist. The research hypothesis is the reason for conducting research. There is a research question that needs to be answered, and researchers believe that what they want to do or study is an answer to that question!
Remember that human beings bring presuppositions and biases into everything they do. This is especially true in applied research and hypothesis testing. It just feels GOOD to find the outcomes/differences/associations that researchers believe exist. And researchers will cut corners and manipulate their data analyses in order to find truth in their hypotheses. This is a good reason for the focus of hypothesis testing being strictly on the null hypothesis. When statistical significance is not achieved when testing the primary hypothesis (p > .05), then it is the null hypothesis that researchers "do not reject," rather than the research hypothesis.
Research hypothesis and between-subjects research design
The research hypothesis is stated in different fashions according to the number of groups being compared in between-subjects research designs.
For between-subjects designs with one group, the research hypothesis states that there is a significant difference between the expected proportion (categorical outcome), median (ordinal outcome), or mean (continuous outcome) and the observed proportion, median, or mean.
For between-subjects designs with two groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the two groups.
For between-subjects designs with three or more groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the three or more groups.
For between-subjects designs with one group, the research hypothesis states that there is a significant difference between the expected proportion (categorical outcome), median (ordinal outcome), or mean (continuous outcome) and the observed proportion, median, or mean.
For between-subjects designs with two groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the two groups.
For between-subjects designs with three or more groups, the research hypothesis states that there is a significant difference between the proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome) of the three or more groups.
Research hypothesis and within-subjects research design
For within-subjects research designs, the research hypothesis is stated in a fashion that reflects the number of observations of an outcome that are being analyzed.
For within-subjects designs with two groups, the research hypothesis states that there is a significant difference between the "pre" and "post" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome).
For within-subjects designs with three groups, the research hypothesis states that there is a significant difference between the "pre," "post," and "maintenance" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome).
For within-subjects designs with two groups, the research hypothesis states that there is a significant difference between the "pre" and "post" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome).
For within-subjects designs with three groups, the research hypothesis states that there is a significant difference between the "pre," "post," and "maintenance" observations of proportions (categorical outcome), medians (ordinal outcome), or means (continuous outcome).
Research hypothesis and correlation design
When writing the research hypothesis for a correlation design, it states that there is a significant association between the two variables that are being correlated. The expected correlation for the research hypothesis is not equal to zero, "0."
Research hypothesis and multivariate design
The research hypothesis for a multivariate design using some form of regression is that the slope is not equal to zero, "0." If there is a significant relationship between variables in a regression model, the slope will not equal zero.
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