Week 3 STAT 288 PDF

S TAT 2 8 8 Week 3​ Chapter 5 and 6​ Dr Abdulla Eid CHAPTER 5 DIRECTORY OF VISUALIZATIONS: 5.1 AMOUNTS: 5.2 DISTRIBUTION: DISTRIBUTION (CONT.): 5.3 PROPORTIONS PROPORTION (CONT.): PROPORTION (CONT.): 5.4 X–Y RELATIONSHIPS: X-Y RELATIONSHIP (CONT.): 5.5 GEOSPATIAL DATA: 5.6 Uncert...

S TAT 2 8 8 Week 3​ Chapter 5 and 6​ Dr Abdulla Eid CHAPTER 5 DIRECTORY OF VISUALIZATIONS: 5.1 AMOUNTS: 5.2 DISTRIBUTION: DISTRIBUTION (CONT.): 5.3 PROPORTIONS PROPORTION (CONT.): PROPORTION (CONT.): 5.4 X–Y RELATIONSHIPS: X-Y RELATIONSHIP (CONT.): 5.5 GEOSPATIAL DATA: 5.6 Uncertainty: Error bars are meant to indicate the range of likely values for some estimate or measurement. They extend horizontally and/or vertically from some reference point representing the estimate or measurement Reference points can be shown in various ways, such as by dots or by bars. Uncertainty (Cont.): Confidence strips provide a clear visual sense of uncertainty but are difficult to read accurately Eyes and half-eyes combine error bars with approaches to visualize distributions (violins and ridgelines, respectively), and thus show both precise ranges for some confidence levels and the overall uncertainty distribution A quantile dot plot can serve as an alternative visualization of an uncertainty distribution UNCERTAINTY (CONT.):  Chapter 6 Visualizing amounts: In many scenarios, we are interested in the magnitude of some set of numbers. For example, we might want to visualize the total sales volume of different brands of cars, or the total number of people living in different cities, or the age of olympians performing different sports. In all these cases, we have a set of categories (e.g., brands of cars, cities, or sports) and a quantitative value for each category. These cases are visualizing amounts, because the main emphasis in these visualizations will be on the magnitude of the quantitative values. The standard visualization in this scenario is the bar plot, which comes in several variations, including simple bars as well as grouped and stacked bars. Alternatives to the bar plot are the dot plot and the heatmap. 6.1 Bar Plot: To motivate the concept of a bar plot: Consider the total ticket sales for the most popular movies on a given weekend. The table on the right shows the top-five weekend gross ticket sales on the Christmas weekend of 2017. The movie “Star Wars: The Last Jedi” was by far the most popular movie on that weekend, outselling the fourth- and fifth-ranked movies “The Greatest Showman” and “Ferdinand” by almost a factor of 10. BAR PLOT (BAR CHART): UGLY (WHY?) BETTER SOLUTION BAD (WHY?) ORDER MATTER (OF SOME SENSE) BAD (WHY?)  Moral Pay attention to the bar order. If the bars represent unordered categories, order them by ascending or descending data value  6.2 Grouped and stacked bars: Example: The U.S. Census Bureau provides median income levels broken down by both age and race. We can visualize this dataset with a grouped bar plot. In a grouped bar plot, we draw a group of bars at each position along the x axis, determined by one categorical variable, and then we draw bars within each group according to the other categorical variable. HARD TO READ! A BIT EASIER? ULTIMATE SOLUTION! EXERCISE: CAN YOU DESCRIBE IT?  6.3 Dot plots and heatmaps: Bars are not the only option for visualizing amounts. One important limitation of bars is that they need to start at zero, so that the bar length is proportional to the amount shown DOTS PLOTS BAD (WHY?) BAD (WHY?) HEATMAP (DATA VALUES ONTO COLOR)