Join Yash Patel for an in-depth discussion in this video Scenario and context, part of SPSS for Academic Research.
- [Instructor] Perhaps one of the simplest statistical tests that you can perform is the classic one sample T-test. The one sample T-test is also called a single parameter test or the single sample T-test. It's used to determine whether a sample comes from a population with a specific mean. This population sometimes is not known but we often have a general idea of what it could be. This test can be used as part of a robust sampling strategy.
If you're trying to generalize results from a sample, you need to be sure that the sample is representative of the population. Let's take a look at our women's heights experiment. If we were to take a sample of women's heights, X bar, and generalize the findings to a population, then we need to make sure that the sample mean is generally acceptable and in line with our predicted population mean which is 64 inches. The one sample T-test can also do the exact thing with a criterion.
For example, instead of comparing the sample mean to the population mean, you can compare the sample mean to a benchmark. In this scenario let's compare a sample of 100 women's heights to the hypothesized population mean that we got earlier, the 64 inches.
- Quantitative vs. qualitative analysis
- Sample size considerations
- Normal distribution
- Estimating the population mean
- One-sample t-test
- Paired-sample t-test
- One-way and two-way ANOVA
- Repeated measure ANOVA
Skill Level Beginner
1. General Notions about Science and Research
2. Quantitative Research Fundamentals
3. One-Sample T-Test
4. Paired-Samples T-Test
5. Balanced One-Way ANOVA
6. Two-Way ANOVA
7. Repeated Measures ANOVA
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