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Course Description:
Business decisions are driven by data and judgment. Everyday
managers and business professionals receive data about their organization,
which they must sort, analyze, and interpret for decision-making
purposes. In addition, they create quantitative models to simulate how
their organizations will perform under a particular set of assumptions or
business conditions.
Unfortunately, decision-makers are often
unable to reach any meaningful conclusions from the information available
because the data is poorly presented and explained. The preparation and
presentation of numbers is filed with opportunities for misuse, from the
fancy graphs that show nonexistent trends to results that are detached
from their method and meaning. Statistics is as much as art as a science
and there is always a possibility of bias when one has an axe to grind, a
point to prove, or a product to sell.
In addition, the decision maker does not
always have technical know-how to question the appropriateness of the
methodology or the assumptions used to analyze the data. An
understanding of how to apply quantitative methods to everyday business
situations can provide managers and business professionals with a valuable
tool to gain insight into the business and make better-informed decisions.
In this seminar, we will review the rational
process for analysis and decision making and how to apply quantitative
methods to justify decisions based on a systematic interpretation of the
data. In the first day of this seminar, we will explain the use of
descriptive statistics to organize data and gain insights into the
business. We will explain the different parameters that can be used
to describe a data set and discuss data characteristics, measures of
central tendency, and measures of variability or dispersion. We will also
explain how to use and graphs to present and communicate data more
effectively.
The second day of this seminar will explain
the basic concepts of how to draw inferences from data using quantitative
methods. We will discuss the use of models and simulation to obtain
insight about the business and shows its real-world application in diverse
settings such as budgeting, forecasting, cost-benefit analysis,
profitability analysis, capacity planning, and standards settings.
Pre-requisites:
This course
is an introductory seminar on how to apply statistical techniques to
analyze and communicate data. It is taught at a basic level. No
pre-requisites are required.
Pre-work: Not required.
Who should attend:
Executive
and middle level managers who need to analyze and interpret data for
decision-making purposes; strategic planners, financial and cost analysts,
controllers, industrial engineers, and any business professional who
analyzes and communicates data for making business decisions.
Course Objectives: Upon
completion of this seminar, the participant should be able to:
- Describe a sample or data set using statistical
parameters.
- Present and communicate data more effectively.
- Analyze, interpret and present the descriptive
parameters in diverse business settings.
- Apply quantitative methods to draw inferences from
data.
- Design business models for improved decision
making.
Course Content:
- The rational process of analysis and decision
making
- Descriptive statistics as a tool to organize and
interpret data
- Distribution and samples
- Describing distributions
- Types of samples
- Measures of central tendency
- Mean
- Median
- Mode
- Weighted average
- Geometric mean
- Measures of variability
- The standard deviation
- The interquartile range
- The range
- How to present and communicate data
- Rules for preparing tables and graphs
- The use of color
- The basics of modeling and simulations
- Montecarlo simulations
- Systems models
- Examples of financial models in everyday
practice
- Drawing inferences from the data
- Probabilities
- Hypothesis testing
- Sample size
- Confidence levels
- Confidence intervals
- Correlation measures
- Regression analysis
Instructional method used:
Group-live
Recommended CPE:
14 credit hours
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