Suppose a certain state university's college of business obtained the following results on the salaries of a recent graduating dass: Finance Majors Business Analytics Majors 120 n2 = = 30 x, = $48,137 X2 = $55,417 %3D s= $19,000 s, = $10,000 (a) Formulate hypotheses so that, if the null hypothesis is rejected, we can conclude that salaries for Finance majors are significantly lower than the salaries of Business Analytics majors. Use a = the population mean salary for Finance majors, and let µ, = the population mean salary for Business Analytics majors. Enter != for # as needed.) 0.05. (Let %3D
Minimization
In mathematics, traditional optimization problems are typically expressed in terms of minimization. When we talk about minimizing or maximizing a function, we refer to the maximum and minimum possible values of that function. This can be expressed in terms of global or local range. The definition of minimization in the thesaurus is the process of reducing something to a small amount, value, or position. Minimization (noun) is an instance of belittling or disparagement.
Maxima and Minima
The extreme points of a function are the maximum and the minimum points of the function. A maximum is attained when the function takes the maximum value and a minimum is attained when the function takes the minimum value.
Derivatives
A derivative means a change. Geometrically it can be represented as a line with some steepness. Imagine climbing a mountain which is very steep and 500 meters high. Is it easier to climb? Definitely not! Suppose walking on the road for 500 meters. Which one would be easier? Walking on the road would be much easier than climbing a mountain.
Concavity
In calculus, concavity is a descriptor of mathematics that tells about the shape of the graph. It is the parameter that helps to estimate the maximum and minimum value of any of the functions and the concave nature using the graphical method. We use the first derivative test and second derivative test to understand the concave behavior of the function.
![Suppose a certain state university's college of business obtained the following results on the salaries of a recent graduating class:
### Salary Data
- **Finance Majors**
- Sample size (\( n_1 \)): 120
- Mean salary (\( \bar{x}_1 \)): $48,137
- Standard deviation (\( s_1 \)): $19,000
- **Business Analytics Majors**
- Sample size (\( n_2 \)): 30
- Mean salary (\( \bar{x}_2 \)): $55,417
- Standard deviation (\( s_2 \)): $10,000
### Hypothesis Testing
(a) **Formulate Hypotheses**
Null Hypothesis (\( H_0 \)):
Alternative Hypothesis (\( H_a \)): [if rejected, conclude salaries for Finance majors are significantly lower than Business Analytics majors. Use \(\alpha = 0.05\)]
(b) **What is the value of the test statistic?**
- Use \(\mu_1 - \mu_2\).
- Round your answer to three decimal places.
(c) **What is the p-value?**
- Round your answer to four decimal places.
(d) **Conclusion**
Options:
- Reject \( H_0 \): Conclude salaries for Finance majors are significantly lower than Business Analytics majors.
- Do not reject \( H_0 \): We cannot conclude salaries for Finance majors are significantly lower than Business Analytics majors.
Choose the appropriate conclusion based on the test results.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F70237df8-dfb4-41d0-af11-e6f29414ce12%2F5955039b-e3cd-45d0-8373-ad02cd288834%2Fhz9304h_processed.jpeg&w=3840&q=75)

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