Applying Business Analytics Course
Overview
Big data and business analytics have the capability to help you operate from a new vantage point. With accessibility and the competency to leverage relevant business information from both inside and outside your corporation, you can succeed in the increasingly competitive marketplace. In this course you will explore external data and its sources that, when integrated into your business analytics, can help you increase efficiencies, develop innovative strategies, optimize processes and more.
Explore how external data and internal data spread across departmental silos and systems can be mined and modeled to solve complex business issues. In this 100% online eight-week course you’ll develop techniques for analyzing social media, geospatial, mobile, location-based, and video and imagery data. With enhanced analysis capabilities you can realize new opportunities and develop innovative solutions you can apply across various functional areas, such as customer service, human resources, marketing, IT and procurement, as well as multiple industries and fields like healthcare, financial services and retail.
What You’ll Learn
Statistics – Data Driven Science
- Distinguish between definite and statistical statements
- Define data, variable, and element
- Identify quantitative and qualitative data
- Visualize data using graphical tools
Data Distribution
- Identify normally distributed data using a histogram
- Calculate percentiles and Z-scores for normally distributed data
- Utilize binomial distribution in business
Statistical Inference
- Identify and define the target parameter of a population
- Distinguish between point and interval estimates
- Construct confidence intervals for mean of a population for a quantitative outcome variable
- Construct confidence intervals for the population proportion for a categorical outcome variable
- Distinguish between when to use various statistical tests, such as t-tests, ANOVA, linear regression, proportion tests, and logistic regression
- Calculate t-tests and one-way independent ANOVA in Excel
- Interpret the results of t-tests and one-way independent ANOVA
Simple Linear Regression
- Create scatter plots showing the relationship between two quantitative variables using Excel and Tableau
- Identify the nature of the relationship between two variables leveraging a scatter plot
- Construct predictions and interpretations for response variables using recession and model
- Utilize Excel and Tableau to calculate a linear regression model
Data Mining and Inferential Statistics
- Identify critical issues associated with preparing, checking and transforming data for data mining
- Explain the use of inferential statistics in data mining
- Master to how apply specific inferential techniques
Decision Trees, Machine Learning and Optimization
- Learn how to apply different machine learning approaches
- Compare and contrast supervised and unsupervised machine learning
- Describe the challenges with successfully deploying recommendations from machine learning projects
Curved Regression Models with Interpretations Involving Percentage Changes:
- Graphically determine if a linear, exponential, logarithmic, or power model appears to accurately represent trends in the data
- Interpret the relationship between predictor and outcome variables when modeled with an exponential, logarithmic, or power model
- Create interpretations involving the relationship between two variables that incorporate percentage changes in one or both variables in the model
- Calculate exponential, logarithmic, and power models in Excel and Tableau
Multiple Linear Regression
- Use a combination of quantitative and categorical predictor variables to predict the value of an outcome variable
- Calculate multiple linear regression models in Excel
Logistic Regression: Predicting a probability of a yes/no outcome:
- Calculate the predicted probability of a yes/no outcome occurring based on a logistic regression model that uses a combination of quantitative and categorical predictor variables as predictor variables
- Distinguish between various measures of accuracy in discriminant analysis
Analyzing Text, Networks, Location and Imagery Data
- Identify text analytics methods, focusing on “words” and, separately, “documents”
- Compare and contrast when and what types of problems network analytics could be used to address
- Understand how and why spatial/temporal analyses, mobile-location based analyses, and image analyses might be conducted
- Describe specific visual techniques available in spreadsheets to meaningfully explore data
Who Should Register?
This course is designed for professionals who want to enhance their analytical competencies. With its exploration into social media and other types of data external to the enterprise, the course helps managers understand how this type of information can be leveraged to develop and enhance long-term business strategies.
Curriculum
8 Week Course
Statistics – Data Driven Science
- Statistics – Data Driven Science – Introduction
- Data and Variables
- Data Visualization
- Statistical Thinking
Describing the Data
- Describing the Data – Introduction
- Mean – Measure of Central Tendency
- Measures of Variability
- Application and Mean of Variance
- Application Using R
- Percentile and Z–score
Data Distribution
- Probability Distributions
- Normal Distribution
- Use of Normal Distribution
- Binomial Distributions
Statistical Inference
- Defining the Target
- Point and Interval Estimators
- Confidence Intervals
- Inference on Two Populations
Simple Linear Regression
- Probabilistic Relation
- Linear Regression – Introduction
- Case Study One: Building Maintenance
- Case Study One: Building Maintenance (Continued)
- Use of R
- Case Study Two: Predicting Facebook Likes From Twitter Data
Data Mining and Inferential Statistics
- Data Mining – Introduction
- Business Understanding
- Framing a Research Question
- Data Understanding and Preparation
- Checking and Transforming Data
- Inferential Data Mining Techniques – Part One
- Inferential Data Mining Techniques – Part Two
Decision Trees, Machine Learning and Optimization
- Machine Learning
- Introduction to Non–Inferential Techniques
- Clustering Techniques
- Decision Trees
- Neural Networks
- Optimization
- Detecting Anomalies
- Machine Learning Closure and Challenges
Analyzing Text, Networks, Location and Imagery Data
- Text Analytics – Part One
- Text Analytics – Part Two
- Network Analysis
- Spatial – Temporal Analysis
- Mobile – Location Based Analysis – Part One
- Mobile – Location Based Analysis – Part Two
- Imagery Analytics
- Redux – Data Visualization
If you’re going to pay by credit card, you can either get started with installment payments or pay in full. Just let your enrollment representative know the option that work best for you.
Corporate and Military Tuition Assistance
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Corporate and Military TA
Corporate tuition assistance is paid by your employer. You will need to provide appropriate forms for processing, prior to enrollment. Air Force tuition assistance is available for active-duty service members. You will need to provide a valid military tuition assistance voucher. Both TA options are subject to employer benefit policies.
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Deferred Corporate TA
Pay tuition now and have your employer reimburse you. Additional documentation will be needed to process this payment. Subject to employer benefit policies.
Military Benefits
Active Duty
Michigan State offers a 15% savings, per certificate course, to active-duty servicemembers, Guardsmen and Reservists (upon verification of military status).
Veterans
Michigan State offers a 15% savings, per certificate course to veterans (upon verification of military status).
Spouses and Family
Michigan State offers a 15% savings, per certificate course, to active-duty servicemembers, veterans, Guardsmen, Reservists and their spouses and dependents (upon verification of military status).
If you are interested in learning more about the steps you need to complete payment, please contact a Student Success Representative. This reduction is valid off the standard tuition fee rate of the listed courses offered by Michigan State University with online administration by Bisk. This reduction is not stackable with other reductions, and you may not use this reduction in conjunction with other reductions.
