Hello, focusing on this week's discussion topic of various statistical tests, as identified in the chart, I selected an independent sample t-test and a one-way ANOVA test to discuss. According to Moore et al. (2021) the role of statistical tests are to analyze relevant statistical data to test hypothesis, observe patterns and to obtain reliable outcomes. Observing the similarities of independent sample t-test and a one-way ANOVA, indicated both statistical tests evaluate the statistical significance of the variations of the central tendency, namely the mean scores (Gravetter & Forzano, 2018). For example, research presented by Latif (2024 )demonstrated the utilization of the statistical test of an independent sample t -test and a one-way ANOVA to examine the same variable. Moreover, both tests focused on determining the variations of work satisfaction in relation to gaining the statistical data of the mean of the dependent variable (Latif, 2024). Additionally, recognizing another similarity of an independent sample t-test and a one-way ANOVA is they both have a Between Subjects design. According to Gravetter and Forzano (2018) several advantages exist in respect of a Between Subjects design and include obtaining independent scores, being readily accessible and being applicable within various research questions.
Thank you,
Lisa Fabian (Smith)
References
Gravetter F.J. & Forzano, L.A.B. (2018). Research Methods for the Behavioral Sciences (10th ed.). Boston, MA: Cengage.
Latif, M.A. (2024). Differences in job satisfaction of male and female teachers in private and public secondary schools.
Discover Psychology, 4 (1), 101. https://doi.org/10.1007/s44202-024-00221-7
Moore, D.S., Notz, W.I., & Fligner, M. (2021). Basic Practice of Statistics (9th ed.). New York, NY : Macmillan Learning.
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Technique |
|
|
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Independent Variable |
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|
|
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Dependent Variable |
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Definition |
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# of IVs |
Fixed or Random |
# of levels in IV (If Fixed) |
Between or Within Subjects |
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# of DVs |
Fixed or Random |
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One Sample t-test |
A statistical test which compares the mean of a group to a known population mean |
|
None |
N/A |
N/A |
N/A |
|
1 Continuous Variable |
Random |
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Independent Samples t-test |
Two groups of different people compared |
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1 (only one manipulation) |
Fixed, people are in one group or the other |
2 (t-tests are always only 2 groups) |
Between (different people in each group) |
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1 (just one outcome per t-test) |
Random (outcome can take on any value) |
|
Paired Samples t-test (AKA repeated measures t-test or dependent measures t-test) |
A statistical test which compares the means of two groups |
|
1 |
Fixed |
2 (the levels ae compared) |
Within-Subjects (the same people are being measured) |
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2 |
Random |
|
One-Way ANOVA |
Compares the means of three or more groups |
|
1 |
Fixed |
3 or more |
Can be either between (Groups) or within subjects (repeated) |
|
1 |
Random |
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Two-Way ANOVA |
A statistical test which compares the mean of two Iv’s in respect of the interaction with the DV |
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2 |
Fixed |
2 levels |
Can be either a Between or Within- subjects Has a tendency to be Between |
|
1 |
Random |
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Repeated Measures ANOVA |
Compares the mean of three or more levels of an IV among the same group |
|
1 |
Fixed |
3 or more |
Within Subjects |
|
1 |
Random |
|
Factorial ANOVA (can also be called a Mixed Factors Factorial ANOVA) |
Observes data from with 1 between subjects and 1 within subjects |
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2 or more |
Fixed |
2 or more |
Both Between and Within Subjects |
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1 (continuous) |
Random |