Need to prove significant difference between the changes in the two groups: control and experimental. What test can show this difference in my SPSS research? And what value should p have to state the fact that difference is absent?
1 comment to Significant difference between two groups
The control group is the group that is having no intervention, out of the ordinary. The Experimental group is the group that will be given procedures, such as shots or a different intervention, to test the results. These results will be compared to the control group.
Throughout an experiment, this will show changes, such as behavior, appearance, in reaction to special treatment to the experimental group, which is not given to the control group. That means the control is used to show the proof of your work. For significant test between control and experiment groups rules are same as other significance test. For instance, T test can use for comparing mean between two groups. The t-test can assess whether the means of two groups are statistically different from each other. If means not all differences between the experimental group and the control group than it can be accepted as supporting the alternative hypothesis. The result needs to differ significantly statistically for the researcher to accept the alternative hypothesis. Similarly, for proportions you can do chi square test.
A statistical significant test normally generates a result between 0 and 1, with 0 showing no correlation between variables, and 1 that there is no chance involved. Of course, values of exactly 0 or 1 are impossible, and are merely the extreme ends of the scale. For example, a statistical test produces a result of 0.834. This indicates that there is a 16.6% probability that any link between the variables is just due to chance. Thus, the 0.95, gives a 5% level of confidence in the results. If your p value found less than 0.05 or 0.001 (confidence level), you should reject the null hypothesis in favor of the alternative. Alternatively, if p is greater than 0.05, you should not reject the null hypothesis.
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The control group is the group that is having no intervention, out of the ordinary. The Experimental group is the group that will be given procedures, such as shots or a different intervention, to test the results. These results will be compared to the control group.
Throughout an experiment, this will show changes, such as behavior, appearance, in reaction to special treatment to the experimental group, which is not given to the control group. That means the control is used to show the proof of your work. For significant test between control and experiment groups rules are same as other significance test. For instance, T test can use for comparing mean between two groups. The t-test can assess whether the means of two groups are statistically different from each other. If means not all differences between the experimental group and the control group than it can be accepted as supporting the alternative hypothesis. The result needs to differ significantly statistically for the researcher to accept the alternative hypothesis. Similarly, for proportions you can do chi square test.
A statistical significant test normally generates a result between 0 and 1, with 0 showing no correlation between variables, and 1 that there is no chance involved. Of course, values of exactly 0 or 1 are impossible, and are merely the extreme ends of the scale. For example, a statistical test produces a result of 0.834. This indicates that there is a 16.6% probability that any link between the variables is just due to chance. Thus, the 0.95, gives a 5% level of confidence in the results. If your p value found less than 0.05 or 0.001 (confidence level), you should reject the null hypothesis in favor of the alternative. Alternatively, if p is greater than 0.05, you should not reject the null hypothesis.