The CEO of ABC manufacturing commissioned a study to look at the differences between the current

salaries of her employees (n = 474) and their starting salaries. The study collected current and beginning
salary data for each of the 474 employees and the researcher conducted a statistic and the results are
presented below. Using the five steps of hypothesis testing, explain what the researcher might have done,
including the appropriate analysis, and interpret the results. Are there any problems with this study? If so,
explain what they are.
Beginning salary mean = $17,016.09, SD = $7,870
Current salary mean = $34,419.57 SD = $17,075
Test statistic = 35.036, p <.05

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To explain what the researcher might have done, including the appropriate analysis, and interpret the results, we will follow the five steps of hypothesis testing.

Step 1: State the hypotheses.
In this case, the study aims to determine if there is a significant difference between the current salaries and the starting salaries of the employees. Therefore, we have two hypotheses:
- Null Hypothesis (H0): There is no significant difference between the current and starting salaries of the employees.
- Alternative Hypothesis (H1): There is a significant difference between the current and starting salaries of the employees.

Step 2: Formulate an analysis plan.
To test these hypotheses, the researcher might have chosen to conduct a paired t-test because the study collected current and beginning salary data for each employee, which creates a paired relationship.

Step 3: Analyze sample data.
The test statistic is provided in the question: t = 35.036, and the significance level is p < .05. With this information, the researcher can compare the test statistic with the critical value from the t-distribution table to determine the p-value.

Step 4: Interpret the results.
Since the p-value is less than the significance level (p < .05), we reject the null hypothesis. This means that there is a significant difference between the current and starting salaries of the employees. The large t-value suggests a strong difference between the means.

Step 5: Generalize the results.
Based on the sample data, the researcher can conclude that there is a significant difference between the current and starting salaries of the employees in ABC Manufacturing. However, it is important to note that these results are only applicable to the participants in the study and may not reflect the entire population.

Now, let's discuss any potential problems with this study:
1. The sample size: The study only collected data from 474 employees. To generalize the results to the entire population, a larger sample size would be more representative.
2. Sampling method: The question doesn't provide information about how the sample was selected. If the sample is not random or representative, it may introduce bias into the results.
3. External factors: The study does not take into account external factors that may impact salary changes, such as promotions, job performance, or changes in job responsibilities. These factors could influence the results and should be considered for a comprehensive analysis.

It is essential to address these potential problems to ensure the validity and generalizability of the study's findings.