Project Week 2 For These Project Assignments Throughout The
Project Week 2for These Project Assignments Throughout The Course You
Project Week 2for These Project Assignments Throughout The Course You
Project Week 2 For these project assignments throughout the course you will need to reference the data in the ROI Excel spreadheet. Download it here. Using the ROI data set: For each of the 2 majors calculate the mean, median, minimum, maximum, range, and standard deviation for the columns ‘Cost’ and ’30-Year ROI’. By hand or with Excel, for each of the 2 majors calculate the probability that a college picked from the column for ‘School Type’ is ‘Private’. By hand or with Excel, for each of the 2 majors find the probability that a college with the ‘School Type’ ‘Private’ has a ’30-Year ROI’ between $1,500,000 and $1,800,000.
Paper For Above instruction
In this analysis, we examine data pertaining to colleges categorized by majors, focusing on financial investment and return on investment (ROI). The dataset sourced from the ROI Excel spreadsheet provides relevant metrics, including 'Cost' and '30-Year ROI', alongside college attributes such as 'School Type' and 'Major'. The primary objectives are to analyze these metrics for two specified majors, compute descriptive statistics, and evaluate probabilistic relationships within the data set.
Understanding the Dataset
The dataset contains various colleges, each associated with specific attributes:
- Major: the academic discipline
- Cost: enrollment or tuition expenses
- 30-Year ROI: the long-term return on investment over three decades
- School Type: classifications such as 'Public' or 'Private'
To proceed, we focus on two majors, designated for this analysis, let's assume these are 'Engineering' and 'Business'. The analysis involves calculating statistical measures, which serve to summarize and understand the distribution of 'Cost' and '30-Year ROI' within these groups.
Descriptive Statistics for Major Groups
The descriptive statistics include measures of central tendency and variability such as mean and median, and measures of spread such as minimum, maximum, range, and standard deviation.
1. Mean: It provides the average value of the data for each metric.
2. Median: This indicates the middle value when the data is ordered.
3. Minimum and Maximum: The smallest and largest values observed.
4. Range: The difference between the maximum and minimum, representing the breadth of the data.
5. Standard Deviation: It measures the dispersion of data points around the mean.
Calculations can be performed manually using formulas or efficiently through Excel functions such as `AVERAGE`, `MEDIAN`, `MIN`, `MAX`, `STDEV.P`, etc.
For the two majors, 'Engineering' and 'Business', we first filter the dataset for each major and then compute these statistics for both 'Cost' and '30-Year ROI'.
Probability of a College Being 'Private'
Next, we compute the probability that a college selected at random from the dataset is a 'Private' school, separately within each major. This is achieved by dividing the number of 'Private' colleges by the total number of colleges in the specific major.
Mathematically:
\[
P(\text{School Type = Private}) = \frac{\text{Number of Private colleges in major}}{\text{Total colleges in major}}
\]
This calculation can be performed manually by counting or via Excel using filters and the `COUNTIF` function.
Probability that a 'Private' College Has ROI Between $1,500,000 and $1,800,000
Lastly, examine the subset of private colleges within each major to find the probability that their '30-Year ROI' falls within the specified range ($1,500,000 to $1,800,000). This involves:
- Filtering the dataset for colleges with 'School Type' equal to 'Private' within each major
- Counting how many of these colleges have '30-Year ROI' within the given interval
- Dividing this count by the total number of private colleges in each major
This probability indicates the likelihood that a private college offers a substantial long-term ROI, providing insights for prospective students and investors.
Implications and Usage of Findings
These statistical measures and probabilities serve multiple purposes:
- Identifying which major has higher typical costs and ROI
- Understanding the distribution and variability within each group
- Assisting prospective students in making data-driven decisions
- Guiding policymakers or educational institutions in resource allocation and strategic planning
The methodology outlined ensures rigorous analysis, whether conducted manually or with the aid of Excel’s computational tools, for comprehensive understanding of the dataset's insights.
Conclusion
This analysis highlights the importance of descriptive and probabilistic statistics in evaluating higher education investments. Performing these calculations enriches our understanding of the financial landscape of colleges based on majors and school types, enabling informed decisions and strategic planning.
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