Recall in Inferential Statistics and Regression Analysis the discussion on correlation and regression analysis. A first step in correlation analysis is to calculate the correlation coefficient (r) for (x, y) data. R provides a built-in function cor() to calculate the correlation coefficient for bivariate data.…
As mentioned earlier, a quick statistical summary can be generated using the summary() command in R, where the usage is summary(data_vector). R has extensive built-in libraries for calculating confidence intervals, hypothesis testing, and working with various probability distributions such as binomial, Poisson, normal,…
R is a statistical analysis tool that is widely used in the data science field. R provides many tools for data exploration, visualization, and statistical analysis. It is available as a free, open-source program and provides an integrated suite of…
Excel provides many statistical functions and statistical distributions that are used in data science applications. Excel Analysis for Measures of Center and Dispersion Excel allows you to type a formula into a cell. Using a formula, you can refer to…
Excel provides many options for generating graphs and other visualizations to assist in data science investigations. The menu in Figure A9 shows some of the many options available within Excel for graphing. Figure A9 A Menu of Various Graphs Available within MS Excel (Used…
A screenshot of the main Excel menu when it is open is provided in Figure A1. As you see, Excel consists of a series of submenus such as Home, Insert, Draw, Page Layout, Formulas, etc. Clicking on each Menu item opens…
LEARNING OUTCOMES: By the end of this section, you should be able to: The executive summary serves as an essential first impression, succinctly transforming complex technical analyses into an accessible and engaging synopsis for an audience of varied backgrounds. The…
LEARNING OUTCOMES: By the end of this section, you should be able to: As discussed in Time Series and Forecasting, modeling is the process of creating a mathematical representation of real-world phenomena to allow for predictions and insights based on data. Modeling involves…
Learning Outcomes By the end of this section, you should be able to: Data scientists should be prepared to explain the research question, the sources of data, the steps in data processing, key analytical techniques and statistical methods employed and…
Figure 10.1 The report is key: When done well, data science reports provide evidence-based insights that promote transparency by documenting methods and assumptions used, help identify risks and opportunities, and support decision-making. (credit: “CC-BY-Mapbox-Uncharted-ERG_Mapbox-b041” by Mapbox/Flickr, CC BY 2.0) Chapter Outline 10.1 Writing…