The question is how do I design a basic experiment that would allow us to establish a cause-effect relationship between number of hours worked per week and lower college graduation rates? It must have these components: a manupulated independent variable, a dependent variable, control for extraneous variables, an experimental group and a conrol group and random sampling and random assignment.

No one is going to do your work for you. Did you bother to read bobpursley's response to your first post?

thank you

To design an experiment that establishes a cause-effect relationship between the number of hours worked per week and lower college graduation rates, you can follow these steps:

1. Identify the Variables:
- Independent Variable (IV): Number of hours worked per week.
- Dependent Variable (DV): College graduation rates.

2. Define the Experimental and Control Groups:
- Experimental Group: This group will consist of participants who work a specific number of extra hours per week on top of their regular workload. For example, they might be required to work an additional 10 hours per week.
- Control Group: This group will consist of participants who do not work any additional hours and maintain their regular workload.

3. Establish Random Sampling:
- Random Sampling involves randomly selecting participants from a larger population to ensure the sample represents the population as a whole. For example, you can randomly select participants from a pool of college students.

4. Implement Random Assignment:
- Random Assignment involves randomly assigning participants to either the experimental or control group. This helps eliminate any bias or systematic differences between the groups. For instance, you can use a random number generator to assign participants to the groups.

5. Control for Extraneous Variables:
- Extraneous variables are any other factors that could potentially affect the DV. To control for these variables, you need to ensure that both groups are as similar as possible, except for the manipulation of the independent variable. This can be done by matching participants based on relevant characteristics (e.g., GPA, gender, etc.) or using statistical techniques such as blocking or stratification during the random assignment process.

6. Data Collection:
- Collect the relevant data on the number of hours worked per week and college graduation rates for both the experimental and control groups. This includes tracking the participants' work hours and monitoring their graduation outcomes.

7. Analyze the Results:
- Once you have collected the data, compare the college graduation rates between the experimental and control groups using statistical analysis methods such as t-tests or analysis of variance (ANOVA). These analyses will help determine if there is a significant difference in graduation rates between the groups, establishing a cause-effect relationship.

By following these steps, you will be able to design a basic experiment that allows you to establish a cause-effect relationship between the number of hours worked per week and lower college graduation rates, while incorporating the necessary components of a manipulated independent variable, a dependent variable, control for extraneous variables, experimental and control groups, and random sampling and random assignment.