In the following lesson, we briefly summarize the various topics.
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.
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.
namely the central limit theorem.
and two discrete distributions, the binomial and the Poisson.
Application of these distributions were worked out using Excel data.
These are statistical tools often used in the industry.
and we saw various applications of the confidence interval estimation using Excel.
for proportions, for differences across means, and so on.
and is the engine that drives the majority of data analytic applications.
Understanding regression analysis and applying it is well worthwhile.
rather than detailed mathematical derivations.
transforming variables, and interaction effects.
easy to understand examples in Microsoft Excel.
You'll be applying all these skills and knowledge gained in the Capstone project.