In the following lesson, we briefly summarize the various topics. We have covered across the four courses in the specialization on Business Statistics and Analysis. We'll be using skills and knowledge developed across all four courses in this Capstone project. The Capstone project that you all will be doing aims at applying the knowledge and skills you have gained over the period of four courses in the specialization on Business Statistics and Analysis. The first of the four courses introduce the use of Excel for data analysis. We began with reading data into Excel and covered many functionality of Excel. We performed various arithmetic data manipulation and presentation functions of Excel. The aim of the course was to give us a good grasp of analyzing data in Excel. That course also explored various graphing and charting abilities of Excel. The second course in the specialization started exploring business statistics using Excel. You all got to know various descriptive measures of data and their calculation in Excel. We learned various measures of central tendency in the data, such as the mean, median, and mode measures. We also studied the measures of dispersion, such as the range, interquartile range, standard deviation, variance; and also measures of covariation between two sets of data. These measures were the covariance and correlation. Excel functions were introduced for these various descriptive statistics. This course then introduce you to the important concepts of probability and random variables. In this context, we introduced the notion of a sample and population and the backbone of all inferential statistics, namely the central limit theorem. This led to our study of statistical distributions, such as the normal or the Bell Curve, and two discrete distributions, the binomial and the Poisson. Application of these distributions were worked out using Excel data. The third course in the specialization introduce you all to confidence intervals and hypothesis testing. These are statistical tools often used in the industry. The t-distribution was introduced in this context, and we saw various applications of the confidence interval estimation using Excel. Different kinds of hypothesis testing were introduced such as hypothesis test for means, for proportions, for differences across means, and so on. The last course in the specialization covered extremely important topic of linear regression analysis. This is perhaps the single most important business statistics tool used in the industry and is the engine that drives the majority of data analytic applications. Understanding regression analysis and applying it is well worthwhile. The focus of this course was on understanding and application rather than detailed mathematical derivations. To the extent possible, we cut out detailed math behind the regression analysis and focused on applications. You got to know various procedures such as dummy variable regressions, transforming variables, and interaction effects. All these were introduced and explained using easy to understand examples in Microsoft Excel. So that was a snapshot of what you all covered in the four course specialization on Business Statistics and Analysis. You'll be applying all these skills and knowledge gained in the Capstone project.
