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Sharad Borle

Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent of ‘risk’ or ‘uncertainty’ in various business processes.

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Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent of ‘risk’ or ‘uncertainty’ in various business processes.

This is the third course in the specialization "Business Statistics and Analysis" and the course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing. We first conceptually understand these tools and their business application. We then introduce various calculations to constructing confidence intervals and to conduct different kinds of Hypothesis Tests. These are done by easy to understand applications.

To successfully complete course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later. Please note that earlier versions of Microsoft Excel (2007 and earlier) will not be compatible to some Excel functions covered in this course.

WEEK 1

Module 1: Confidence Interval - Introduction

In this module you will get to conceptually understand what a confidence interval is and how is its constructed. We will introduce the various building blocks for the confidence interval such as the t-distribution, the t-statistic, the z-statistic and their various excel formulas. We will then use these building blocks to construct confidence intervals.

Topics covered include:

• Introducing the t-distribution, the T.DIST and T.INV excel functions

• Conceptual understanding of a Confidence Interval

• The z-statistic and the t-statistic

• Constructing a Confidence Interval using z-statistic and t-statistic

WEEK 2

Module 2: Confidence Interval - Applications

This module presents various business applications of the confidence interval including an application where we use the confidence interval to calculate an appropriate sample size. We also introduce with an application, the confidence interval for a population proportion. Towards the close of module we start introducing the concept of Hypothesis Testing.

Topics covered include:

• Applications of Confidence Interval

• Confidence Interval for a Population Proportion

• Sample Size Calculation

• Hypothesis Testing, An Introduction

WEEK 3

Module 3: Hypothesis Testing

This module introduces Hypothesis Testing. You get to understand the logic behind hypothesis tests. The four steps for conducting a hypothesis test are introduced and you get to apply them for hypothesis tests for a population mean as well as population proportion. You will understand the difference between single tail hypothesis tests and two tail hypothesis tests and also the Type I and Type II errors associated with hypothesis tests and ways to reduce such errors.

Topics covered include:

• The Logic of Hypothesis Testing

• The Four Steps for conducting a Hypothesis Test

• Single Tail and Two Tail Hypothesis Tests

• Guidelines, Formulas and an Application of Hypothesis Test

• Hypothesis Test for a Population Proportion

• Type I and Type II Errors in a Hypothesis

WEEK 4

Module 4: Hypothesis Test - Differences in Mean

In this module, you'll apply Hypothesis Tests to test the difference between two different data, such hypothesis tests are called difference in means tests. We will introduce the three kinds of difference in means test and apply them to various business applications. We will also introduce the Excel dialog box to conduct such hypothesis tests.

Topics covered include:

• Introducing the Difference-In-Means Hypothesis Test

• Applications of the Difference-In-Means Hypothesis Test

• The Equal & Unequal Variance Assumption and the Paired t-test for difference in means.

• Some more applications

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What's inside

Syllabus

Confidence Interval - Introduction
Confidence Interval - Applications
Hypothesis Testing
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Hypothesis Test - Differences in Mean

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Sharad Borle, who are recognized for their work in Business Statistics
Applies hypothesis tests to test the difference between two different data
Develops mastery over confidence intervals and hypothesis tests, which are important tools for business decision making
May not be suitable for learners who are unfamiliar with Microsoft Excel

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Business Applications of Hypothesis Testing and Confidence Interval Estimation with these activities:
Complete Probability and Statistics Prerequisite Review
Refresh the skills and knowledge covered in a prerequisite probability and statistics course, especially if it has been a while since taking the class.
Browse courses on Probability
Show steps
  • Review notes and textbooks from the prerequisite course
  • Do practice problems from the textbook
  • Take practice quizzes or mock exams
Understanding Hypothesis Testing
There are many tutorials available online for hypothesis testing. This activity will help develop a conceptual understanding of hypothesis testing's various aspects.
Browse courses on Hypothesis Testing
Show steps
  • Search for online tutorials on hypothesis testing, e.g., YouTube, Coursera, edX
  • Follow the tutorial, take notes, and complete any practice exercises
  • Summarize the key concepts in a short outline or mind map
Worksheet on Confidence Intervals
Practice applying the concepts of calculating and interpreting confidence intervals using relevant formulas and data.
Browse courses on Confidence Intervals
Show steps
  • Find a worksheet or practice problems on confidence intervals
  • Work through the problems carefully, showing your work
  • Check your answers against the provided solutions
Five other activities
Expand to see all activities and additional details
Show all eight activities
Hypothesis Testing Practice Problems
Solving practice problems helps improve your understanding of hypothesis testing procedures and strengthen your problem-solving abilities.
Browse courses on Hypothesis Testing
Show steps
  • Find practice problems related to hypothesis testing
  • Solve the problems, following the steps of hypothesis testing
  • Compare your answers with solutions or ask for feedback from peers/instructors
Develop an Infographic on Hypothesis Testing
Creating an informative infographic provides a visual summary of hypothesis testing concepts, aiding in memorization and reinforcing understanding.
Browse courses on Hypothesis Testing
Show steps
  • Gather key information and data on hypothesis testing
  • Design the infographic using visually appealing and easy-to-understand graphics
  • Present the infographic to peers or mentors for feedback
Attend Workshop on Business Hypothesis Testing
Attending a workshop on business hypothesis testing will provide exposure to real-world applications and allow you to interact with experts.
Browse courses on Hypothesis Testing
Show steps
  • Research and identify relevant workshops on business hypothesis testing
  • Register and attend the workshop
  • Actively participate in discussions and Q&A sessions
Kaggle Competition in Data Analysis and Hypothesis Testing
Participating in a Kaggle competition provides a practical and challenging opportunity to solve a real-world data problem involving hypothesis testing.
Browse courses on Hypothesis Testing
Show steps
  • Identify a relevant Kaggle competition related to hypothesis testing
  • Join the competition and form a team or work individually
  • Develop and implement a data analysis and hypothesis testing approach
Mentor Students in Hypothesis Testing
Mentoring others helps reinforce your own understanding of hypothesis testing and allows you to share your knowledge with others.
Browse courses on Hypothesis Testing
Show steps
  • Identify opportunities to mentor students or colleagues
  • Set clear goals and expectations for the mentoring relationship
  • Provide guidance, support, and feedback on hypothesis testing concepts

Career center

Learners who complete Business Applications of Hypothesis Testing and Confidence Interval Estimation will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists leverage statistical analysis and machine learning techniques to extract insights from data. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for evaluating the reliability and validity of their models. By developing a strong understanding of statistical analysis, Data Scientists can make more informed decisions, develop more accurate models, and contribute to advancements in various fields, such as healthcare, finance, and technology.
Survey Researcher
Survey Researchers design, conduct, and analyze surveys to collect data on various topics. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for ensuring the accuracy and reliability of their surveys. By developing proficiency in statistical analysis, Survey Researchers can design more effective surveys, analyze data more accurately, and draw valid conclusions from their findings.
Quantitative Analyst
Quantitative Analysts utilize statistical modeling and analysis to make predictions and inform investment decisions. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for developing and evaluating quantitative models. By enhancing their statistical skills, Quantitative Analysts can improve the accuracy of their predictions and contribute to the success of their clients.
Machine Learning Engineer
Machine Learning Engineers design, develop, and implement machine learning models. This course can provide them with foundational knowledge in confidence interval estimation and hypothesis testing, which are essential for evaluating the performance and reliability of their models. By enhancing their statistical skills, Machine Learning Engineers can develop more robust and effective models, contributing to advancements in various fields, such as artificial intelligence, computer vision, and natural language processing.
Actuary
Actuaries use statistical and mathematical methods to assess risk and uncertainty in insurance, finance, and other fields. This course can provide them with foundational knowledge in confidence interval estimation and hypothesis testing, which are essential for evaluating the probability and financial impact of future events. By enhancing their statistical skills, Actuaries can develop more accurate and reliable models, contributing to sound decision-making and risk mitigation strategies.
Business Intelligence Analyst
Business Intelligence Analysts leverage data analysis techniques to extract insights from business data. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for evaluating the significance and reliability of their findings. By developing proficiency in statistical analysis, Business Intelligence Analysts can make more informed decisions and contribute to the development of data-driven strategies that drive business success.
Statistician
Statisticians apply statistical methods to collect, analyze, interpret, and present data. This course can enhance their understanding of confidence interval estimation and hypothesis testing, which are fundamental to the practice of statistics. By developing a strong foundation in statistical analysis, Statisticians can contribute to advancements in various fields, such as healthcare, finance, and social sciences.
Econometrician
Econometricians use statistical methods to analyze economic data and test economic theories. This course can provide them with a strong foundation in confidence interval estimation and hypothesis testing, which are essential for conducting economic research and making informed policy decisions. By developing proficiency in statistical analysis, Econometricians can contribute to a deeper understanding of economic phenomena and support evidence-based policymaking.
Operations Research Analyst
Operations Research Analysts utilize statistical analysis to improve business processes and operations. This course can provide them with the knowledge and skills to construct confidence intervals and conduct hypothesis tests, which are crucial for evaluating the effectiveness of process improvements and making data-driven decisions. By strengthening their statistical skills, Operations Research Analysts can optimize business operations and contribute to increased efficiency and profitability.
Risk Manager
Risk Managers assess and mitigate financial and operational risks faced by organizations. This course can equip them with the skills to construct confidence intervals and conduct hypothesis tests, which are crucial for evaluating the likelihood and impact of potential risks. By developing proficiency in statistical analysis, Risk Managers can make more informed decisions and implement effective risk management strategies, protecting organizations from potential losses.
Data Analyst
Data Analysts leverage statistical analysis to extract insights from large datasets. This course can equip them with the skills to construct and interpret confidence intervals and perform hypothesis testing, which are essential for drawing accurate conclusions from data. By developing a solid foundation in statistical analysis, Data Analysts can enhance their ability to identify patterns, predict outcomes, and communicate data-driven insights to stakeholders.
Biostatistician
Biostatisticians use statistical methods to analyze and interpret data in the field of healthcare. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for conducting clinical trials and evaluating the safety and efficacy of medical treatments. By developing proficiency in statistical analysis, Biostatisticians can contribute to the development of new and improved healthcare interventions and treatments.
Financial Analyst
Financial Analysts utilize statistical analysis to evaluate financial data and make investment decisions. This course can enhance their ability to construct confidence intervals and conduct hypothesis tests, which are crucial for assessing the risk and return of investment portfolios. By strengthening their statistical skills, Financial Analysts can make more informed investment decisions and contribute to the success of their clients.
Market Researcher
Market Researchers rely on statistical analysis to understand consumer behavior and market trends. This course can provide them with a foundation in confidence interval estimation and hypothesis testing, which are essential for conducting market research studies and interpreting the results. By developing proficiency in statistical analysis, Market Researchers can increase the accuracy and reliability of their research findings, leading to more effective marketing campaigns and product development.
Business Analyst
Business Analysts are often involved in the analysis and interpretation of market research data. This course can equip them with confidence interval estimation and hypothesis testing skills, which they can apply to critically evaluate data and make informed recommendations to stakeholders. By developing a strong understanding of statistical analysis, Business Analysts can enhance their ability to identify trends, forecast outcomes, and assess the effectiveness of business strategies.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Business Applications of Hypothesis Testing and Confidence Interval Estimation .
Focuses on business applications of statistical methods and provides accessible, step-by-step guidance in a wide range of data analysis techniques. It also includes chapters on the latest statistical methods and updates on business applications.
This practical guide provides a step-by-step approach to using Excel for data analysis in business. It covers a wide range of techniques, from data cleaning and manipulation to statistical analysis and visualization.
This easy-to-follow guide provides step-by-step instructions on how to use Excel for statistical analysis. It covers a wide range of topics, from descriptive statistics to hypothesis testing and regression analysis.
Provides a comprehensive overview of hypothesis testing using IBM SPSS Statistics. It covers a wide range of topics, from basic concepts to advanced statistical techniques.
Provides a non-technical overview of data science and its applications in business. It covers a wide range of topics, from data collection and cleaning to data analysis and visualization.

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