Category: Statistics

Data Analysis And Business AnalyticsCompetency

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Competency 3 Statement
Utilizing statistical regression and time series analysis models, you will be able to evaluate and analyze how multiple variables impact an organization. You
will also be able to create forecasts and interpret data to analyze performance as it impacts strategic planning and comparative advantage for an
organization.
Manipulating data to create models helps us describe and summarize relationships between variables. Understanding how variables relate to each other
helps businesses predict performance and make informed strategic plans. For example, to make an informed recommendation to management regarding
which types of office buildings to acquire or sell, you would model the relationship between assessed value and given variables.
This reflection gives you an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models, and then reflect on office
buildings you recommend acquiring and selling, and why.
Pre-Reflection Exercise
Download the Competency 3 Reflection Data Set. The data set is information about the tax assessment value assigned to medical office buildings in a city.
The following is a list of the variables in the database:
Floor Area: square feet of floor space
Offices: number of offices in the building
Entrances: number of customer entrances
Age: age of the building (years)
Assessed Value: tax assessment value (thousands of dollars)
As you work through the following exercises, note your answers to the given questions so you can easily summarize them in your reflection.
Use the data set to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics.
1. Construct a scatter plot in Excel with Floor Area as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear
regression equation and R2 in your graph.
Do you observe a linear relationship between the 2 variables?
2. Use Excels Analysis ToolPak to conduct a regression analysis of Floor Area and Assessment Value.
Is Floor Area a significant predictor of Assessment Value?
3. Construct a scatter plot in Excel with Age as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear
regression equation and R2 in your graph.
Do you observe a linear relationship between the 2 variables?
4. Use Excels Analysis ToolPak to conduct a regression analysis of Age and Assessment Value.
Is Age a significant predictor of Assessment Value?
Construct a multiple regression model.
Use Excels Analysis ToolPak to conduct a regression analysis with Assessment Value as the dependent variable and Floor Area, Offices, Entrances, and Age
as independent variables.
What is the overall fit R2? What is the adjusted R2?
Which predictors are considered significant if we work with α=0.05? Which predictors can be eliminated?
What is the final model if we only use Floor Area and Offices as predictors?
Suppose our final model is: Assessed Value = 115.9 + 0.26 x Floor Area + 78.34 x Offices.
What would be the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago?

Data Analysis And Business Analytics

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Utilizing statistical probability models, you will be able to evaluate and analyze business data under uncertainty conditions. You will also be able to create and test hypotheses and draw conclusions based on samples of data.
Reflection
Consider the following:
Many business activities generate data that can be thought of as random. An example described in the textbook is the servicing of cars at an oil change
shop. Each car entering the shop can be considered an experiment with random outcomes. A variable of interest in this experiment could be the amount of
time necessary to service the car. Service time will vary randomly with each car. Often, we can capture the most relevant characteristics of a stochastic
process with a simple probability distribution model. We can then analyze the model to make predictions and drive decisions. For instance, we could
estimate the number of technicians the oil change shop needs to service demand on a Saturday afternoon.
Respond to the following questions:
What is a random variable?
How would you differentiate a discrete from a continuous random variable?
A laptop manufacturing company has implemented a 2-step process to test the quality of each production batch. In the first step, a technician randomly
selects 15 laptops from the batch and determines whether they meet specifications. The batch is considered acceptable provided no more than 1 laptop fails
to meet specifications. Otherwise, the entire batch has to be tested in the second step. Historical data shows that 95% of the laptops produced adhere to
specifications.
Reflect on the following in a minimum of 500 words:
What are the 4 characteristics of a binomial experiment?
Can we use a binomial distribution to model this process?
What is the probability that the entire batch unnecessarily has to be tested if in fact 95% of its laptops conform to specifications? (Hint: Use Excels
=BINOMDIST() function to find the probability)
What is the probability that the batch is incorrectly accepted if only 75% of its laptops actually conform to specifications?
What situations in your organization might this type of analysis apply to? Explain.

 

 

Preparing to implement a strategic change initiative

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Leaders face many difficult ethical choices as they develop and implement their strategic change initiatives. Many of these ethical challenges are ethical dilemmas that result from competing stakeholder rights such as employees versus shareholders, not issues of unethical behavior. What is the one ethical dilemma that concerns you the most as a leader preparing to implement a strategic change initiative? Why? How might you address this dilemma? Why would you select this approach?

Preparing to implement a strategic change initiative

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Leaders face many difficult ethical choices as they develop and implement their strategic change initiatives. Many of these ethical challenges are ethical dilemmas that result from competing stakeholder rights such as employees versus shareholders, not issues of unethical behavior. What is the one ethical dilemma that concerns you the most as a leader preparing to implement a strategic change initiative? Why? How might you address this dilemma? Why would you select this approach?

Change and management

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It isn’t the changes that do you in, it’s the transitions. Change is not the same as transition. Change is situational: the new site, the new boss, the new team roles, the new policy. Transition is the psychological process people go through to come to terms with the new situation. Change is external, transition is internal. (William Bridges).

Discussion: How does a person’s attitude and assumptions about “human nature” in general affect his or her leadership approach? How might a leader’s attitude about him or herself alter or reinforce this approach?

Change and management

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It isn’t the changes that do you in, it’s the transitions. Change is not the same as transition. Change is situational: the new site, the new boss, the new team roles, the new policy. Transition is the psychological process people go through to come to terms with the new situation. Change is external, transition is internal. (William Bridges).

Discussion: How does a person’s attitude and assumptions about “human nature” in general affect his or her leadership approach? How might a leader’s attitude about him or herself alter or reinforce this approach?