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Reporting t-test results is a crucial aspect of statistical analysis, as it allows researchers to accurately communicate the findings of their study. The t-test is a statistical test used to determine whether there is a significant difference between the means of two groups. When reporting t-test results, it is important to include the t-value, degrees of freedom, and p-value. The t-value represents the difference between the two groups, while the degrees of freedom indicate the number of observations in the sample. The p-value indicates the probability of obtaining the observed results by chance. Additionally, it is important to provide a brief interpretation of the results, such as whether there is a significant difference between the two groups or not. Including examples of the t-test results can further clarify the findings and make them more easily understandable for the reader. Overall, reporting t-test results accurately and clearly is essential for the proper communication and understanding of the statistical analysis.
Report T-Test Results (With Examples)
We can use the following general format to report the results of a :
A one sample t-test was performed to compare [variable of interest] against the population mean.
The mean value of [variable of interest] (M = [Mean], SD = [standard deviation]) was significantly [higher, lower, or different] than the population mean; t(df) = [t-value], p = [p-value].
We can use the following format to report the results of an :
A two sample t-test was performed to compare [response variable of interest] in [group 1] and [group 2].
There [was or was not] a significant difference in [response variable of interest] between [group1] (M = [Mean], SD = [standard deviation]) and [group2] (M = [Mean], SD = [standard deviation]); t(df) = [t-value], p = [p-value].
We can use the following format to report the results of a :
A paired samples t-test was performed to compare [response variable of interest] in [group 1] and [group 2].
There [was or was not] a significant difference in [response variable of interest] between [group1] (M = [Mean], SD = [standard deviation]) and [group2] (M = [Mean], SD = [standard deviation]); t(df) = [t-value], p = [p-value].
Note: The “M” in the results stands for sample mean, the “SD” stands for sample standard deviation, and “df” stands for degrees of freedom associated with the t-test statistic.
The following examples show how to report the results of each type of t-test in practice.
Example: Reporting Results of a One Sample T-Test
A botanist wants to know if the mean height of a certain species of plant is equal to 15 inches. She collects a random sample of 12 plants and performs a one sample-test.
The following screenshot shows the results of the test:
Here’s how to report the results of the test:
A one sample t-test was performed to compare the mean height of a certain species of plant against the population mean.
The mean value of height (M = 14.33, SD = 1.37) was not significantly different than the population mean; t(11) = -1.685, p = .120.
Example: Reporting Results of an Independent Samples T-Test
Researchers want to know if a new fuel treatment leads to a change in the average miles per gallon of a certain car. To test this, they conduct an experiment in which 12 cars receive the new fuel treatment and 12 cars do not.
The following screenshot shows the results of the independent samples t-test:
Here’s how to report the results of the test:
A two sample t-test was performed to compare miles per gallon between fuel treatment and no fuel treatment.
There was not a significant difference in miles per gallon between fuel treatment (M = 22.75, SD = 3.25) and no fuel treatment (M = 21, SD = 2.73); t(22) = -1.428, p = .167.
Example: Reporting Results of a Paired Samples T-Test
Researchers want to know if a new fuel treatment leads to a change in the average mpg of a certain car. To test this, they conduct an experiment in which they measure the mpg of 12 cars with and without the fuel treatment.
The following screenshot shows the results of the paired samples t-test:
Here’s how to report the results of the test:
A paired samples t-test was performed to compare miles per gallon between fuel treatment and no fuel treatment.
There was a significant difference in miles per gallon between fuel treatment (M = 22.75, SD = 3.25) and no fuel treatment (M = 21, SD = 2.73); t(11) = -2.244, p = .046.
Use the following calculators to automatically perform various t-tests:
Cite this article
stats writer (2024). How do I report t-test results, including examples?. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/stats/how-do-i-report-t-test-results-including-examples/
stats writer. "How do I report t-test results, including examples?." PSYCHOLOGICAL SCALES, 30 Apr. 2024, https://scales.arabpsychology.com/stats/how-do-i-report-t-test-results-including-examples/.
stats writer. "How do I report t-test results, including examples?." PSYCHOLOGICAL SCALES, 2024. https://scales.arabpsychology.com/stats/how-do-i-report-t-test-results-including-examples/.
stats writer (2024) 'How do I report t-test results, including examples?', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/stats/how-do-i-report-t-test-results-including-examples/.
[1] stats writer, "How do I report t-test results, including examples?," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, April, 2024.
stats writer. How do I report t-test results, including examples?. PSYCHOLOGICAL SCALES. 2024;vol(issue):pages.