Decision Analysis for Managers: Excel, Data Analysis, and Reporting
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Homework Assignment
AI Summary
This document presents a comprehensive solution to a Decision Analysis for Managers assignment, addressing both Module 1 and Module 2 exercises. Module 1 focuses on Excel-based calculations, including the appropriate use of STDEV.S versus STDEV.P, and applying formulas to calculate tax withholdings and tax breaks using IF statements. Module 2 delves into data visualization and analysis, exploring the use of time series plots and histograms to analyze AIG's share price data from 2002 to 2013. The solution analyzes the features of the data visible in each graphical display, assesses the suitability of each display for reporting to AIG's CEO, and provides insights into the company's performance and investment recommendations. References to relevant academic articles are also included to support the analysis.

Running head: DECISION ANALYSIS FOR MANAGERS 1
DECISION ANALYSIS FOR MANAGERS
DECISION ANALYSIS FOR MANAGERS
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DECISION ANALYSIS FOR MANAGERS
Table of Contents
MODULE 1.....................................................................................................................................3
Exercise 1.....................................................................................................................................3
Explain why you would use STDEV.S instead of STDEV.P?.................................................3
MODULE 2.....................................................................................................................................3
Exercise 2.....................................................................................................................................3
What features of the data can you see in the time series plot?.................................................3
What features of the data can you see in the histogram?.........................................................3
Which graphical display seems the more appropriate for a report to the CEO of AIG?..........3
References........................................................................................................................................4
Table of Contents
MODULE 1.....................................................................................................................................3
Exercise 1.....................................................................................................................................3
Explain why you would use STDEV.S instead of STDEV.P?.................................................3
MODULE 2.....................................................................................................................................3
Exercise 2.....................................................................................................................................3
What features of the data can you see in the time series plot?.................................................3
What features of the data can you see in the histogram?.........................................................3
Which graphical display seems the more appropriate for a report to the CEO of AIG?..........3
References........................................................................................................................................4

DECISION ANALYSIS FOR MANAGERS
MODULE 1
Exercise 1
Explain why you would use STDEV.S instead of STDEV.P?
Standard deviation is a term that can be understood as the measure of the magnitude of
deviations between values and its observations. Further, it is bifurcated as the standard deviation
of the population and standard deviation of a sample set. As the name suggests, STDEV.S is a
used on a particular sample set and STDEV.P is used on the entire population. In the present case
standard deviation is required to be calculated for females only and hence the formula of
STDEV.S is used (Albatineh, et al 2018).
MODULE 2
Exercise 2
What features of the data can you see in the time series plot?
A time plot displays the values against the time. Though they are similar to xy graphs, but
the difference is xy graph can literally display a variety of x variables whereas the time plots can
only display time on the x-axis. The goal of this graph is to find the patterns of AIG’s share price
from a period of 2002-2013 (Wang, et al 2017).
What features of the data can you see in the histogram?
A histogram is one of the most important tools which are constructed to summarize
discrete or continuous data. It is often used to display the data in the form of range. As in the
MODULE 1
Exercise 1
Explain why you would use STDEV.S instead of STDEV.P?
Standard deviation is a term that can be understood as the measure of the magnitude of
deviations between values and its observations. Further, it is bifurcated as the standard deviation
of the population and standard deviation of a sample set. As the name suggests, STDEV.S is a
used on a particular sample set and STDEV.P is used on the entire population. In the present case
standard deviation is required to be calculated for females only and hence the formula of
STDEV.S is used (Albatineh, et al 2018).
MODULE 2
Exercise 2
What features of the data can you see in the time series plot?
A time plot displays the values against the time. Though they are similar to xy graphs, but
the difference is xy graph can literally display a variety of x variables whereas the time plots can
only display time on the x-axis. The goal of this graph is to find the patterns of AIG’s share price
from a period of 2002-2013 (Wang, et al 2017).
What features of the data can you see in the histogram?
A histogram is one of the most important tools which are constructed to summarize
discrete or continuous data. It is often used to display the data in the form of range. As in the
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DECISION ANALYSIS FOR MANAGERS
current scenario, the bins are formed for the share price of AIG Company and the gaps between
the bars reflect that the values are discrete in nature. Further, it is a feasible option as a histogram
can also help detect any unusual observations (outliers) or any gaps in the data (Stelzl, et al
2017).
Which graphical display seems the more appropriate for a report to the CEO of AIG?
When analyzing the appropriateness of the graph for AIG, histogram is more feasible
than time series plot as histogram is a power tool to study the outcome of the process. It also
reveals about the data spread and how well the prices are working and whether they are
fluctuating or not. It not only reveals the present performance but also has the ability to analyze
the future performance (Qian, et al 2018). Overall the trend of AIG states that earlier the prices
were closing at a round about 1450 but now the prices have declined to $8 after recession period.
There after the company tried to lift up and still the last closing price of the stock is 33.95% and
this reveals that the performance of the company is growing but at a very slow pace. Hence,
investors are requested to study the data for next two more months and must invest after that.
current scenario, the bins are formed for the share price of AIG Company and the gaps between
the bars reflect that the values are discrete in nature. Further, it is a feasible option as a histogram
can also help detect any unusual observations (outliers) or any gaps in the data (Stelzl, et al
2017).
Which graphical display seems the more appropriate for a report to the CEO of AIG?
When analyzing the appropriateness of the graph for AIG, histogram is more feasible
than time series plot as histogram is a power tool to study the outcome of the process. It also
reveals about the data spread and how well the prices are working and whether they are
fluctuating or not. It not only reveals the present performance but also has the ability to analyze
the future performance (Qian, et al 2018). Overall the trend of AIG states that earlier the prices
were closing at a round about 1450 but now the prices have declined to $8 after recession period.
There after the company tried to lift up and still the last closing price of the stock is 33.95% and
this reveals that the performance of the company is growing but at a very slow pace. Hence,
investors are requested to study the data for next two more months and must invest after that.
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DECISION ANALYSIS FOR MANAGERS
References
Albatineh, A. N., Wilcox, M. L., Zogheib, B., & Kibria, G. B. (2018). Improved confidence
interval estimation of the population standard deviation using ranked set sampling: A
simulation study. Journal of Biostatistics and Epidemiology, 4(3), 173-183.
Qian, Q., Li, Z., Zhao, P., Chen, W., Yin, H., & Zhao, L. (2018). Publishing graph node strength
histogram with edge differential privacy. In International Conference on Database
Systems for Advanced Applications (pp. 75-91). Springer, Cham.
Stelzl, L. S., Kells, A., Rosta, E., & Hummer, G. (2017). Dynamic histogram analysis to
determine free energies and rates from biased simulations. Journal of chemical theory
and computation, 13(12), 6328-6342.
Wang, Y., Han, F., Zhu, L., Deussen, O., & Chen, B. (2017). Line graph or scatter plot?
automatic selection of methods for visualizing trends in time series. IEEE transactions on
visualization and computer graphics, 24(2), 1141-1154.
References
Albatineh, A. N., Wilcox, M. L., Zogheib, B., & Kibria, G. B. (2018). Improved confidence
interval estimation of the population standard deviation using ranked set sampling: A
simulation study. Journal of Biostatistics and Epidemiology, 4(3), 173-183.
Qian, Q., Li, Z., Zhao, P., Chen, W., Yin, H., & Zhao, L. (2018). Publishing graph node strength
histogram with edge differential privacy. In International Conference on Database
Systems for Advanced Applications (pp. 75-91). Springer, Cham.
Stelzl, L. S., Kells, A., Rosta, E., & Hummer, G. (2017). Dynamic histogram analysis to
determine free energies and rates from biased simulations. Journal of chemical theory
and computation, 13(12), 6328-6342.
Wang, Y., Han, F., Zhu, L., Deussen, O., & Chen, B. (2017). Line graph or scatter plot?
automatic selection of methods for visualizing trends in time series. IEEE transactions on
visualization and computer graphics, 24(2), 1141-1154.
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