Effective Data Visualization for Statistics Presentations
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The document provides guidance on effectively summarizing data through tables and graphs. It outlines key principles such as using the appropriate type of graphic for the data, clearly labeling all components, and indicating the source and sample size. The goal is to present information in a clear, concise and visually compelling manner for the intended audience. Examples are given of different types of tables and graphs and how to properly construct and interpret them.
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Effective Data Visualization for Statistics Presentations
- 1. 13/07/2018 Introduction to Statistics 1
- 2. Learning objectives 13/07/2018 Introduction to Statistics 2 By the end of this session, participants should be able to: 1. Understand different ways of summarizing data 2. Choose the right table/graph for the right data and audience 3. Ensure that graphics are self-explanatory 4. Create graphs and tables that are attractive
- 3. Do you present yourself like this?
- 4. So why would you present your data like this?
- 6. This is Better! 6 Use of ITNs in Zambia
- 7. Effective presentation • Clear • Concise • Actionable • Attractive
- 8. Effective presentation • For all communication formats it is important to ensure that there is: • Consistency • Font, Colors, Punctuation, Terminology, Line/ Paragraph Spacing • An appropriate amount of information • Less is more • Appropriate content and format for audience • Scientific community, Journalist, Politicians
- 9. Summarizing data • Tables • Simplest way to summarize data • Data are presented as absolute numbers or percentages • Charts and graphs • Visual representation of data • Data are presented as absolute numbers or percentages 13/07/2018 Introduction to Statistics 9
- 10. Basic guidance when summarizing data • Ensure graphic has a title • Label the components of your graphic • Indicate source of data with date • Provide number of observations (n=xx) as a reference point • Add footnote if more information is needed 13/07/2018 Introduction to Statistics 10
- 11. Tables: Frequency distribution Year Number of cases 2000 4 216 531 2001 3 262 931 2002 3 319 339 2003 5 338 008 2004 7 545 541 2005 9 181 224 2006 8 926 058 2007 9 610 691
- 12. Year Number of malaria cases (n) Relative frequency (%) 2000 4 216 531 8 2001 3 262 931 6 2002 3 319 339 7 2003 5 338 008 10 2004 7 545 541 15 2005 9 181 224 18 2006 8 926 058 17 2007 9 610 691 19 Total 51 400 323 100.0 Percent contribution of reported malaria cases by year between 2000 and 2007, Kenya Source: WHO, World Malaria Report 2009 Tables: Relative frequency
- 13. number of values within an interval *100 total number of values in the table 13/07/2018 Introduction to Statistics 13 Tables: Relative frequency
- 14. Tables: Relative frequency 13/07/2018 Introduction to Statistics 14 Percentage of births by decade between 1900 and 1929 Year Number of births (n) Relative frequency (%) 1900–1909 35 27 1910–1919 46 34 1920–1929 51 39 Total 132 100.0 Source: U.S. Census data, 1900–1929.
- 15. Charts and graphs • Charts and graphs are used to portray: • Trends, relationships, and comparisons • The most informative are simple and self-explanatory 13/07/2018 Introduction to Statistics 15
- 16. Use the right type of graphic • Charts and graphs • Bar chart: comparisons, categories of data • Histogram: represents relative frequency of continuous data • Line graph: display trends over time, continuous data (ex. cases per month) • Pie chart: show percentages or proportional share
- 18. Bar Chart Source: Quarterly Country Summaries, 2008 56 77 66 70 38 45 57 46 0 20 40 60 80 100 Country 1 Country 3 Country 4 Country 5 Percent Household Ownership of at Least 1 Net or ITN, 2008 Any net LLIN
- 19. Stacked bar chart 36 26 9 9 11 20 0 20 40 60 80 100 2008 2007 Percent Year ACT Quinine Amodiaquine Sulfadoxine-Pyrimethamine Chloroquine Other % Children <5 with Fever who Took Specific Antimalarial, 2007-2008
- 20. Histogram 0 2 4 6 8 10 12 14 16 18 20 2000 2001 2002 2003 2004 2005 2006 2007 Percent Percent contribution of reported malaria cases by year between 2000 and 2007, Kenya Relative Frequency
- 21. Line graph 0 1 2 3 4 5 6 Year 1 Year 2 Year3 Year 4 Numberofclinicians Clinic1 Clinic2 Clinic3 *Includes doctors and nurses. Number of Clinicians* Working in Each Clinic During Years 1-4, Country Y
- 22. Caution: Line Graph 0 1 2 3 4 5 6 Clinic1 Clinic2 Clinic3 Numberofclinicians Year 1 Year 2 Year 3 Year 4 Number of Clinicians* Working in Each Clinic During Years 1-4, Country Y *Includes doctors and nurses.
- 23. Pie chart 5923 10 8 MalariaCases 1stQtr 2nd Qtr 3rd Qtr 4th Qtr
- 24. Pie chart 59%23% 10% 8% 1stQtr 2nd Qtr 3rd Qtr 4th Qtr N=257 Percentage of all confirmed malaria cases treated by quarter, Country X, 2011
- 25. Summary • Make sure that you present your data in a consistent format • Use the right graph for the right data and the right audience • Label the components of your graphic (title, axis) • Indicate source of data and number of observations (n=xx) • Add footnote for more explanation
Editor's Notes
- Speaker notes Do you present yourself like this? [HAVE AUDIENCE ANSWER QUESTION.] Why would you not present yourself like this? Do you think this man is taken seriously? What do you think would happen if he tried to speak to someone in the Ministry of Health about some information related to a BCC campaign? Would he even be let in? So, if you know that you would not be taken seriously if you presented yourself like this, then . . .
- Speaker notes Why would you present your data like this? Would most people be able to get the message from this data if it was presented in this STATA output? [ALLOW COMMENTS] No, it is too busy and it is difficult to interpret. The way you present your data can greatly affect how usable the data will be.
- Speaker notes And why would you present your data like this? Can anyone tell me what some problems may be with this chart? POSSIBLE ANSWERS No title No axis labels The colors are difficult to read. (You should never put a dark color on a dark background.) The green color is too bright.
- Speaker notes What is improved in this slide compared to the last one? (other than the data points themselves) POSSIBLE ANSWERS Title Axis labels Data labels The colors are easy to read.
- Speaker notes Regardless what communication formats you use, the information should be presented in a clear, concise way with key findings and recommendation that are actionable.
- Speaker notes An appropriate amount of information will be determined by your audience and format. Policymakers may do better with direct and concise summaries of key points, whereas the scientific community will want more detail. On a PowerPoint slide, try to limit to six lines with no more than six words per line, balance text with graphics, and make sure that there are not too many slides. One way to ensure that you create consistent materials is to decide on a template for the document/presentation/graph, etc., before you produce it. You can then give these guidelines to the different people involved in the process, and then only have to do minor formatting at the end.
- The two main ways of summarizing data are by using tables and charts or graphs. A table is the simplest way of summarizing a set of observations. A table has rows and columns containing data, which can be in the form of absolute numbers or percentages, or both. Charts and graphs are visual representations of numerical data and, if well designed, will convey the general patterns of the data.
- To make your graphics as self-explanatory as possible, there are several things to always include: Every table or graph should have a title or heading The x- and y-axes of a graph should be labeled – include value labels, such as a percentage sign; include a legend Always cite the source of your data and put the date of data were collection or publication Provide the sample size or the number of people to which the graph is referring (N) Include a footnote if the graphic isn’t self-explanatory These points will pre-empt questions and explain the data. In the next several slides, we’ll see examples of these points.
- Speaker notes Frequency distribution is a set of classes or categories along with numerical counts that correspond to each one such as number cases in a given year. What should be added to this table to provide the reader with more information? POSSIBLE ANSWERS Better labels-What type of cases? Malaria cases Title reference Source of text on tables and graphs: Pagano M and Gavreau K. Principles of Biostatistics. 1993.
- Speaker notes In this table, we already had the total number of observations (or n) in the second column but we added a title and the source of the data. Note that this table includes both a title and a reference. The citation is one area where it is acceptable to have typeface that is fairly small in relation to the rest of the text. You do want to have the citation on the slide so that people can know where the data is from if they want that information, but the citation is not the most important part of the slide. You want to draw attention to the data, not the citation itself. We also added relative frequencies to this table. Relative frequency is the percentage of the total number of observations that appear in that interval. It is computed by dividing the number of values within an interval by the total number of values in the table then multiplying by 100. It is the same as computing a percentage for the interval. To analyze this table, we should look at the relative frequencies. What do they tell us? There is an increasing trend in the number of reported malaria cases and in the relative frequency of cases. Does this mean that there is an increase in malaria cases? What would this say about our programs? It is important to take into account what we already know when interpreting these data. We know that since 2000 there has been an increased effort towards malaria control. During this time period, the quality of treatment has improved and the quality of routine information systems has improved. When taking this knowledge into account how would we interpret these data? From 2000-2007, the number of reported malaria cases increased. This may not reflect an actual increase in cases, but an increase in care seeking and reporting. Due to improved case outcomes seen after the introduction of ACTs in Kenya in 2004, individuals with fever began to seek care at formal medical facilities at higher rates. Furthermore, the routine information system improved during this period of time and thus reported more complete information. Source of text on tables and graphs: Pagano M and Gavreau K. Principles of Biostatistics. 1993.
- Another common way to summarize data is with relative frequency – which is the percentage of the total number of observations that appear in that interval. It is computed by dividing the number of values within an interval by the total number of values in the table, then multiplying by 100 to get the percentage. In this table, you see the proportion of the total number of births between 1990 and 1929 (132) by 10-year intervals. The calculation for the first relative frequency is: 35/132 = 0.265 x 100 = 26.5 (approx 27%).
- To interpret this table, we should look at the relative frequencies. What do they tell us? We can see data across the three decades and what percentage of births occurred in each one. The largest percentage of children were born between 1920 and 1929, compared to the other two decades. We can interpret the data further by calculating the average or the mean number of births across 30 years. This will give us a summary of the data.
- Although they are easier to read than tables, charts provide less detail. The loss of detail may be replaced by a better understanding of the data.
- Speaker notes We’re going to review the most commonly used charts and graphs in Excel/PowerPoint. Later we’ll have you use data to create your own graphics which may go beyond those presented here. Bar charts are used to compare data across categories. A histogram looks similar to a bar chart but is a statistical graph that represents the frequency of values of a quantity by vertical rectangles of varying heights and widths. The width of the rectangles is in proportion to the class interval under consideration, and their areas represent the relative frequency of the phenomenon in question A histogram is a histogram, not just because the bars touch. In the bar graph bars in a bar graph can touch if you want them to ... but they don't have to. Touching bars in a bar graph doesn't mean anything. In a histogram, however, the bars must touch. This is because the data elements we are recording are numbers that are grouped, and form a continuous range from left to right. There are no gaps in the numbers along the bottom axis. This is what makes a histogram. Line graphs display trends over time, continuous data (ex. cases per month) Pie charts show percentages or the contribution of each value to a total. When there are more than 4 categories it is best to go to a bar chart so that it is readible
- Speaker notes In this bar chart we’re comparing the categories of data which are any net or ITN. What should be added to this chart to provide the reader with more information? Add a title and data labels. You could also add the source of the data but it isn’t necessary if all of your tables and graphs are derived from the same source/dataset. On the next slide we see how the graph has been improved and is now self-explanatory.
- Speaker notes Note that this chart has a title, axis labels , data labels, and a source. It is best if you limit the bars to 4-8 to keep it readable, especially if it is to be used in a PowerPoint presentation.
- Speaker notes A stacked bar chart is often used to compare multiple values when the values on the chart represent durations or portions of an incomplete whole, such as the percentage of children taking each type of medication for fever when not all children received medication at all.
- Speaker notes This is a histogram. At first glance, histograms look a lot like bar charts. Both are made up of columns and plotted on a graph. However, there are some key differences. The major difference is in the type of data presented on the x (horizontal) axis. With bar charts, each column represents a group defined by a categorical variable. This variable could be types of sports, different football teams, health facilities, or provinces. These are all categories. A histogram presents quantitative variables; the groups on the chart are always made up of numbers or something that could be turned into numbers. This could be age, height, weight, the number of minutes women wait in a queue, years, or months of the year. These groupings are sometimes called “bins.” The bin label can be a single value or a range of values. For example, you could split out the time spent waiting in line by the minute (5 minutes, 6 minutes, 7 minutes) or you could split it into chunks (less than 5 minutes, 6-10 minutes, 11-15 minutes).
- Speaker notes A line graph should be used to display trends over time and is particularly useful when there are many datapoints. In this case we have 4 datapoints for each clinic. By adding a label to the y-axis, a title and a footnote. In some settings, clinicians may only mean doctors but to be clear the footnote let’s the reader know that in this case we are referring to both doctors and nurses.
- Speaker notes What is wrong with this line graph? If you look closely you can see that the X axis should be years, but instead it is clinics. Make sure that the right data is always charted on the axes, or else you may end up with a graph that cannot be interpreted like this one.
- Speaker notes A pie chart displays the contribution of each value to a total. In this chart, the values always add up to 100. What should be added to this chart to provide the reader with more information? What should be changed about this chart to make it more readible? POSSIBLE ANSWERS The color scheme, which is currently too bright The title should be more specific and indicate whether these are numbers or percentages. If these are percentages, that should be listed on the data and the n, or number of cases should be indicated to provide context.
- Speaker notes A pie chart displays the contribution of each value to a total. In this case we used the chart to show contribution of each quarter to the entire year. For example, the first quarter contributed the largest the percentage of enrolled patients. To improve the understanding of the pie chart, we’ve added a more descriptive title and added value labels. On the previous chart, we couldn’t tell if the values are numbers or percentages. Adding the sample size let’s us know the total number of observations. For example It is also important to have charts that are attractive, easy to look at and easy to read. The chart on the previous page was so colorful that it was distracting, the colors were so bright that it was hard to look at the chart, let alone read it. While these colors are not the most interesting, they let the reader focus on the chart. The last chart was an exaggeration, but be sure to make sure that you do not make the same mistake on a smaller level. Limit the slices to 4-6. For extra pizzazz, contrast the most important slice either with color or by exploding the slice.
- Speaker notes In summary, [READ BULLETS]