商业统计与分析专项课程

Business Statistics and Analysis

Build Data Analysis and Business Modeling Skills. Gain the ability to apply statistics and data analysis tools to various business applications.

莱斯大学

Coursera

商业管理

简单(初级)

2 个月

课程概况

The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques. You’ll master essential spreadsheet functions, build descriptive business data measures, and develop your aptitude for data modeling. You’ll also explore basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions. The Specialization culminates with a Capstone Project in which you’ll apply the skills and knowledge you’ve gained to an actual business problem.

To successfully complete all course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later.

To see an overview video for this Specialization, click here!

包含课程

课程1
Introduction to Data Analysis Using Excel

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This is an introductory course in the use of Excel and is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics later. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly but at a peripheral level and wish to enhance their skills. The course takes you from basic operations such as reading data into excel using various data formats, organizing and manipulating data, to some of the more advanced functionality of Excel. All along, Excel functionality is introduced using easy to understand examples which are demonstrated in a way that learners can become comfortable in understanding and applying them. To successfully complete course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later.

课程2
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions

The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course. To successfully complete course assignments, students must have access to Microsoft Excel.

课程3
Business Applications of Hypothesis Testing and Confidence Interval Estimation

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.

课程4
Linear Regression for Business Statistics

Regression Analysis is perhaps the single most important Business Statistics tool used in the industry. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. This is the fourth course in the specialization, "Business Statistics and Analysis". The course introduces you to the very important tool known as Linear Regression. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects. All these are introduced and explained using easy to understand examples in Microsoft Excel. The focus of the course is on understanding and application, rather than detailed mathematical derivations. Note: This course uses the ‘Data Analysis’ tool box which is standard with the Windows version of Microsoft Excel. It is also standard with the 2016 or later Mac version of Excel. However, it is not standard with earlier versions of Excel for Mac.

课程5
Business Statistics and Analysis Capstone

The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available ‘Housing Data’ to pose various questions typically a client would pose to a data analyst. Your job is to do the relevant statistical analysis and report your findings in response to the questions in a way that anyone can understand. Please remember that this is a Capstone, and has a degree of difficulty/ambiguity higher than the previous four courses. The aim being to mimic a real life application as close as possible.

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完成注册课程后,您可以学习专项课程中的所有课程,并且完成作业后可以获得证书。如果您只想阅读和查看课程内容,可以免费旁听该课程。如果您无法承担课程费用,可以申请助学金。

此课程是 100% 在线学习吗?是否需要现场参加课程?

此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

完成专项课程后我会获得大学学分吗?

此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

完成专项课程需要多长时间?

The Specialization is 16 weeks long, plus the additional Capstone Project time.

What background knowledge is necessary?

The specialization will be at an introductory level.

Do I need to take the courses in a specific order?

It is recommended that the courses are taken in the order Course 1 "Introduction to Data Analysis Using Excel", Course 2 "Basic Data Descriptors and Data Distributions and Application to Business Decisions", Course 3 "Business Applications of Hypothesis Testing and Confidence Interval Estimation", and then Course 4 "Linear Regression and Its Application to Business".

What will I be able to do upon completing the Specialization?

You will be able to comfortably use spreadsheets to analyze business data in terms of various descriptive and graphical measures.

You will also be able to conduct statistical analysis of data to test various business propositions using hypothesis testing, and learn to estimate confidence intervals to facilitate business decisions under uncertain circumstances.

You will be able to translate a business decision in terms of a cause and effect regression model, estimate the model using a spreadsheet, and draw inferences regarding operational and strategic implications of the estimated model.

Overall, you will begin the pathway towards transforming yourself into thoughtful, data-driven management decision maker.

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