Data Presentation Techniques - BIOMET PDF

FC20103 BIOMETRIC DATA PRESENTATION INTRODUCTION 3 METHODS OF DATA PRESENTATION COMMON TYPES OF DATA PRESENTATION 7 STEPS TO PRESENT YOUR DATA DATA PRESENTATION USING EXCEL 1 INTRODUCTION Data are usually collected in a raw format; inherent information is difficult to understand. Therefore, raw...

FC20103 BIOMETRIC DATA PRESENTATION INTRODUCTION 3 METHODS OF DATA PRESENTATION COMMON TYPES OF DATA PRESENTATION 7 STEPS TO PRESENT YOUR DATA DATA PRESENTATION USING EXCEL 1 INTRODUCTION Data are usually collected in a raw format; inherent information is difficult to understand. Therefore, raw data need to be summarized, processed, and analyzed. However, no matter how well manipulated, the information derived from the raw data should be presented in an effective format  3 METHODS OF DATA PRESENTATION Textual Tabular Diagrammatic Use words to describe the Using a table to share large Displaying data uses diagrams relationship between amounts of information. and images. information. Organize data in rows and The most visual type for data Enables us to share information columns according to the presentation. that cannot display on graph characteristics of the data. Can share more information Includes paragraphs and words, Useful in comparing data and about the relationships between rather than tables or graphs to helps visualize information. variables in the data set. show data.  Example 1: Forest area in Africa, South America, North and Central America is decreasing between 1990 and 2020, whereas forest area in Asia, Europe and Oceania is increasing. Textual Example 2: In the Biometrics class of 228, 10 obtained the score of above 80. Seventy-seven percent students got a score of 70 and above, while only 4 got 35 and below. Generally, the students performed well in the test. Tabular Tabular Data Qualitative classification: Qualities including, nationality, age, social status, appearance, and personality traits may appear in a table to review and compare sociological and psychological information. Quantitative classification: This category includes items you can count or number. Spatial classification: This applies to situations where information uses a basis of location, such as data on a city, state or region. Temporal classification: Time is the variable in this category, so any measure of time, including, seconds, hours, days or weeks, may help classify the data. Diagrammatic  Diagrammatic Data Pictograms: This diagram uses Cartograms: Any type of map that images to represent data. For shares the location of a person, example, to show the number of place or object. For example, trees planted at Sfera, you may cartograms help navigate theme draw 5 trees, where 1 tree parks so you can find attractions, represent 100 trees. food and gift shops. Bar graphs: Depicts numerical Pie charts: Data appears as a values and uses rectangles to fraction in a circle with few display data for variables in your variables. research. Spatial visualization Tables vs Graphics (Diagrammetrics) Tables Graphics are generally best if you want are best for illustrating trends to be able to look up specific and making comparison information or if the values must be reported precisely. Table number Title Body of the table Column headings or captions Unit Notes Sources if relevant Table number Title Body of the table Unit Column Headings/ captions Note Source (if relevant) 5 Principles of Good Graphs Show the data clearly Use simplicity in design of the graphs Use alignment of a common scale Keep the visual encoding transparent Use standard forms that work COMMON TYPES OF DATA PRESENTATION Histogram Stem plot Box plot Pie chart Scatter Line Ogive plot graph To display data from one quantitative variable graphically, we can use either a histogram or boxplot. There are two simple graphical displays for visualizing the distribution of one categorical variable (Example: Pie Charts and Bar Charts) 5.1 Histogram Histogram is to break the range of values into intervals and count how many observations fall into each interval. When describing the shape of a distribution, we should consider: Symmetry/skewness of the distribution. Peakedness (modality) - the number of peaks (modes) the distribution has. A distribution is called symmetric if, as in the histograms above, the distribution forms an approximate mirror image with respect to the center of the distribution.  The center of the distribution is easy to locate and both tails of the distribution are the approximately the same length. The overall pattern of the distribution of a quantitative variable is described by its shape, center, and spread. By inspecting the histogram or boxplot, we can describe the shape of the distribution, but we can only get a rough estimate for the center and spread.  A distribution is called skewed A distribution is called skewed right if, as in the histogram left if, as in the histogram above, above, the right tail (larger the left tail (smaller values) is values) is much longer than much longer than the right tail the left tail (small values). (larger values). 5.2 Stemplot The stemplot (also called stem and leaf plot) is another graphical display of the distribution of quantitative variable. Source://www.statology.org, 2023 5.3 Boxplot Box plots visually show the distribution of numerical data and skewness by displaying the data quartiles (or percentiles) and averages. Box plots show the five-number summary of a set of data: including the minimum score, first (lower) quartile, median, third (upper) Source://www.simplypsychology.org, 2023 quartile, and maximum score. Definition Minimum Score: The lowest score, excluding outliers (shown at the end of the left whisker). Lower Quartile: Twenty-five percent of scores fall below the lower quartile value (also known as the first quartile). Median: The median marks the mid-point of the data and is shown by the line that divides the box into two parts (sometimes known as the second quartile). Half the scores are greater than or equal to this value, and half are less. Upper Quartile: Seventy-five percent of the scores fall below the upper quartile value (also known as the third quartile). Thus, 25% of data are above this value. Maximum Score: The highest score, excluding outliers (shown at the end of the right whisker). Whiskers: The upper and lower whiskers represent scores outside the middle 50% (i.e., the lower 25% of scores and the upper 25% of scores). The Interquartile Range (or IQR): The box plot shows the middle 50% of scores (i.e., the range between the 25th and 75th percentile). Source://www.simplypsychology.org, 2023 Source://www.simplypsychology.org, 2023 Source://www.simplypsychology.org, 2023 How to Compare Box Plots Step 1: Compare the medians of box plots Source: //blog.bioturing.com, 2018 How to Compare Box Plots Step 2:. Compare the interquartile ranges and whiskers of box plots, look for potential outliers How to Compare Box Plots Step 3: : Look for signs of skewness 5.4 Pie Chart A pie chart (or a circle chart) is a circular statistical graphic which is divided into slices to illustrate numerical proportion. In a pie chart, the arc length of each slice (and consequently its central angle and area), is proportional to the quantity it represents. Source://data.mongabay.com, 2023 5.5 Ogive An ogive, sometimes called a cumulative frequency polygon, is a type of frequency polygon that shows cumulative frequencies. In other words, the cumulative percents are added on the graph from left to right. An ogive graph plots cumulative frequency on the y-axis and class boundaries along the x-axis. 5.6 Scatter Plot Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation. (5-7) Line graph A line graph, also known as a line chart, is a type of chart used to visualize the value of something over time. The line graph consists of a horizontal x-axis and a vertical y- axis. 5.6 Scatter Plot Scatter plots are similar to line graphs in that they use horizontal and vertical axes to plot data points. However, they have a very specific purpose. Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation.  7 STEPS TO PRESENT YOUR DATA 1 Organize your data 2 Identify your audience 3 Choose your presentation style Label your data 4 Introduce your research 5 Focus on main data points 6 Summarise DATA PRESENTATION USING EXCEL