WEEK 4 Here are examples of topics for business … You'll need to complete this step for each course in the Specialization, including the Capstone Project. • Interaction effects in a Regression If you cannot afford the fee, you can apply for financial aid. Module 1: Basic Data Descriptors Overall, you will begin the pathway towards transforming yourself into thoughtful, data-driven management decision maker. The value of a sample statistic such as the sample mean (X) is likely to be different for each sample that is drawn from a population. • Histograms. Examples of discrete distributions include: A continuous probability distribution can assume an infinite number of different values. Menu. The module also introduces the notion of errors, residuals and R-square in a regression model. This module introduces various Excel functions to organize and query data. Topics covered include: Regression analysis is based on several strong assumptions about the variables that are being estimated. Measures of dispersion include variance/standard deviation and percentiles/quartiles/interquartile range. 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. • Sample versus population data; the Central Limit Theorem. The two basic types of regression analysis are: Simple regression analysis: Used to estimate the relationship between a dependent variable and a single independent variable; for example, the relationship between crop yields and rainfall. This module presents different hypothesis tests you could do using the Regression output. • Use of Pivot tables with categorical as well as numerical data • The log-log and semi-log regression models. • Using the Regression model to make predictions Check with your institution to learn more. These descriptive measures summarize and present data using a few numbers. International business research topics provide students a unique chance to write on global business topics, not just business issues that concerns one country. © 2020 Coursera Inc. All rights reserved. You will be able to comfortably use spreadsheets to analyze business data in terms of various descriptive and graphical measures. Do I need to take the courses in a specific order? In this module you will get to conceptually understand what a confidence interval is and how is its constructed. • Introducing the Difference-In-Means Hypothesis Test The science of statistics uses regression analysis, hypothesis testing, sampling distributions, and more to ensure accurate data analysis. Module 2: Descriptive Measures of Association, Probability, and Statistical Distributions Module 4: Hypothesis Test - Differences in Mean It is also standard with the 2016 or later Mac version of Excel. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. Main page Topics Business tendency Business tendency. In this module, you'll see various applications of the Normal distribution. The science of statistics uses regression analysis, hypothesis testing, sampling distributions, and more to […] • VLOOKUP across worksheets • Probability and random variables; discrete versus continuous data This module introduces Hypothesis Testing. Samples are randomly chosen from populations. 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". To successfully complete course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later. Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. The process for computing this is exactly the same; you add up all the elements in the sample and divide by the size of the sample. Questions … • Data filtering in Excel Module 1: Regression Analysis: An Introduction This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You’ll learn how to set filters in data to selectively access data. A very powerful data summarizing tool, the Pivot Table, is also explained and we begin to introduce the charting feature of Excel. Topics covered include: We then introduce various calculations to constructing confidence intervals and to conduct different kinds of Hypothesis Tests. We will introduce the three kinds of difference in means test and apply them to various business applications. 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: However, it is not standard with earlier versions of Excel for Mac. • Transformation of variables Statistics is simply the study of numerical data, facts, figures and measurements. • The Normal distribution (bell curve), NORM.DIST, NORM.INV functions in Excel In statistics, the mean, median, and mode are known as measures of central tendency; they are used to identify the center of a data set: Mean: The value between the largest and smallest values of a data set, obtained by a prescribed method. Statistics make it possible to analyze real-world business problems with actual data so that you can determine if a marketing strategy is really working, how much a company should charge for its products, or any of a million other practical questions. 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. Module 1: Introduction to Spreadsheets The p-values are introduced along with goodness of fit measures R-square and the adjusted R-square. • Hypothesis testing in a Linear Regression Multiple regression analysis: Used to estimate the relationship between a dependent variable and two or more independent variables; for example, the relationship between the salaries of employees and their experience and education. The interquartile range represents the middle 50 percent of the data; it’s calculated as the third quartile minus the first quartile. This is the fourth course in the specialization, "Business Statistics and Analysis". That’s because your topic should attract the attention of your reader and relate to the broad field of business law. Regression analysis is used to estimate the strength and the direction of the relationship between two linearly related variables: X and Y. X is the “independent” variable and Y is the “dependent” variable. Topics covered include: The course
This courses introduces students to a range of statistical techniques that are appropriate in business practice and decision making. We will build a regression model and estimate it using Excel. A business law topic is not easy to find. This information may relate to objects, subjects, activities, phenomena, or regions of space. By Nate Rand. WEEK 4 Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. WEEK 3 We first conceptually understand these tools and their business application. Consider the following examples of mean: This formula simply tells you to add up all the elements in the population and divide by the size of the population. • Formatting rows and columns You'll be prompted to complete an application and will be notified if you are approved. So, a sample measure, such as the mean, should be a good estimate of the corresponding population measure. A powerful regression extension known as ‘Interaction variables’ is introduced and explained using examples. WEEK 4 As such, you should narrow down your topic to something more focused. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Module 3: Introduction to Filtering, Pivot Tables, and Charts • Conceptual understanding of a Confidence Interval ________________________________________ To get started, click the course card that interests you and enroll. When you’re working with populations and samples (a subset of a population) in business statistics, you can use three common types of measures to describe the data set: central tendency, dispersion, and association.By convention, the statistical formulas used to describe population measures contain Greek letters, while the formulas used to describe sample measures contain Latin letters. You get to understand the notion of causation versus correlation. • Hypothesis Testing, An Introduction Random variables and probability distributions are two of the most important concepts in statistics. The module then introduces the notion of probability and random variables and starts introducing statistical distributions. Examples are worked out to re-inforce various concepts introduced. To successfully complete course assignments, students must have access to Microsoft Excel. • Building a Regression Model and estimating it using Excel • Interpretation of coefficients and p-values in the presence of Dummy variables You will also get introduced to the Binomial and Poisson distributions. According to a key result in statistics known as the Central Limit Theorem, the sampling distribution of the sample mean is normal if one of two things is true: Two moments are needed to compute probabilities for the sample mean; the mean of the sampling distribution equals: The standard deviation of the sampling distribution (also known as the standard error) can take on one of two possible values: This is the appropriate choice for a “small” sample; for example, the sample size is less than or equal to 5 percent of the population size. • Making inferences using the estimated model The Topics of Business Statistics Notes are as follows- Unit-1: Probability Theory- Basic Concepts and Approaches, Rules or Theorems-Addition Rule, Multiplication Rule, Complement Rule, Conditional Probability, Bayes Theorem. The test statistic and critical values are used to determine if the null hypothesis should be rejected. 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