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In this study scenario, the clinical psychologist is investigating whether family background—specifically, whether a couple comes from a divorced or intact family—affects marital satisfaction. The psychologist's hypothesis setup is as follows:

1. **Null Hypothesis (\(H_0\))**: There is no difference in relationship satisfaction scores between couples from divorced families and couples from intact families. Mathematically, we can express this as:
   \[
   H_0: \mu_{\text{divorced}} = \mu_{\text{intact}}
   \]
   where \( \mu_{\text{divorced}} \) represents the mean satisfaction score for couples from divorced families, and \( \mu_{\text{intact}} \) represents the mean satisfaction score for couples from intact families.

2. **Alternative Hypothesis (\(H_1\))**: Couples from divorced families have lower relationship satisfaction scores than couples from intact families. This can be expressed as:
   \[
   H_1: \mu_{\text{divorced}} < \mu_{\text{intact}}
   \]

### Key Points in Hypothesis Testing
To analyze the data and test these hypotheses, the psychologist would likely use a statistical test for comparing two means, such as a **t-test** for independent samples. Here are some assumptions that need to be met for this test:

- **Normality**: Scores are assumed to be normally distributed.
- **Equality of Variances**: Variances of satisfaction scores are assumed to be equal between the two groups.

If the data meet these assumptions, the psychologist could conduct a one-tailed t-test to determine if there's a statistically significant difference in satisfaction scores between the two groups.

Would you like details on the next steps for performing the hypothesis test or more on interpreting potential outcomes?

### Further Questions:
1. How would the psychologist determine if the variances between the groups are indeed equal?
2. What might be some confounding factors affecting relationship satisfaction that could be controlled for in this study?
3. If the hypothesis test finds no significant difference, what could be some reasons for this result?
4. What other methods could the psychologist use to measure relationship satisfaction aside from the Marital Satisfaction Inventory?
5. How might the psychologist account for cultural or socio-economic differences in relationship satisfaction?

#### Tip:
In hypothesis testing, always define your hypotheses clearly before gathering data, as it helps clarify the direction and purpose of your study.

Suppose a clinical psychologist sets out to investigate the impact of family origin (divorced vs. intact families) on marital satisfaction. He measures satisfaction using the Marital Satisfaction Inventory in couples from divorced and intact families. The psychologist hypothesizes that couples from divorced families will have lower satisfaction scores than those from intact families. Formulate the null and alternative hypotheses.

Explore a hypothesis testing example where a psychologist investigates the effect of family origin on marital satisfaction. This study compares satisfaction scores between couples from divorced and intact families using a t-test. Understand the statistical approach, null and alternative hypotheses, and assumptions required for the analysis.

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