Presentation of Data PDF

Presentation of Data Prof. Dr. Hanan Mohamed Hathout Type of data  Qualitative or categorical data Examples of Ordinal Data : Examples of nominal data: When companies ask satisfaction Eye color, on a scale of 1 to 10 Gender, Letter grades in the ex...

Presentation of Data Prof. Dr. Hanan Mohamed Hathout Type of data  Qualitative or categorical data Examples of Ordinal Data : Examples of nominal data: When companies ask satisfaction Eye color, on a scale of 1 to 10 Gender, Letter grades in the exam (A, B, C, Hair color, D, F) Religion, Economic Status (High, Medium, and Low) Marital status, etc. Education Level (Higher, Secondary, Primary)  Quantitative or numerical data Examples of Discrete Data )‫ (منفصةل‬: Examples of continuous )‫(متصةل‬Data : Total numbers of students present Temperature of room in a class The weight of a person Numbers of employees in a company length of an object, etc The total number of players who participated in a competition Days in a week Discrete Data Continuous Data Discrete data are countable and finite; Continuous data are measurable; they are in they are whole numbers or integers the form of fractions or decimal Discrete data are represented mainly by Continuous data are represented in the form bar graphs of a histogram Discrete data have spaces between the Continuous data are in the form of a values continuous sequence Examples: Total students in a class, Examples: scores on exam, body weight number of days in a week Quiz 1 A Likert scale, where respondents indicate their level of satisfaction (e.g., strongly disagree to strongly agree), is an example of: A) Nominal data B) Interval data C) Ordinal data D) Ratio data Quiz 2 The number of students in a class is an example of: A) Continuous data B) Nominal data C) Ordinal data D) Discrete data Quiz 3 The average score on a test, where the scores can range from 0 to 100, is an example of: A) Nominal data B) Ordinal data C) Continuous data D) Discrete data Quiz 3 An example of nominal data is: A) Age of participants B) Favorite colors C) Scores on a test D) Distance traveled Methods of presentations of data Tabular presentations Graphical presentations Mathematical presentations Tabular Presentation Requirements of the table: 1- The table should be as simple as possible and should be self explanatory. 2- The table should include a space for certain notes. 3- The title of the table: Should be on the top and answer what, from where and how the data were taken?  How to draw a table The variables are classified into a suitable number of groups and the corresponding value of observations is added against each group. For quantitative studies, find the range (the difference between the smallest and largest observations) and divide into a suitable number of groups with a reasonable class interval. The class interval should not be too small or too big. All intervals should be of the same width. The classes should be clearly defined and each observation must belong to only one class interval. Interval classes must be inclusive and nonoverlapping.  A clear heading is put for each column of the table, and specify the unit of measurement (e.g. kg for weight, cm for height and years or months for age), and the basis of the rate column (percent, per 1000...). The table ends by "Total" (sometimes cannot be given), to be followed by neglected observations not included in the data, if any e. g. drop out cases. Title heading is written at top of table, to define precisely the contents Simple frequency distribution table Problem: The Below observations are the weights of students attending the teaching class in the 4th year in MUST Faculty of medicine 2022. 85, 85, 65, 65, 67, 50, 100, 90, 80, 60, 82, 85. Question: Represent these data in a suitable table? The most suitable table is :The simple frequency distribution table.  Simple frequency distribution table Title : weights of students attending the teaching class in the 4th year in MUST Faculty of medicine 2022. Weight in Kg Frequency 50 – 60 (kg) 1 60 – 70 (kg) 4 70 – 80 (kg) 0 80 – 90 (kg) 4 90- 100 (kg) 3 Total 12 85, 85, 65, 65, 67, 50, 100, 90, 80, 60, 82, 85  Percent or relative frequency distribution table Weight in Kg Frequency Percent 50 – 60 (kg) 1 8.3 60 – 70 (kg) 4 33.3 70 – 80 (kg) 0 zero 80 – 90 (kg) 4 33.3 90- 100 (kg) 3 25 Total 12 100.0 Weights : 85, 85, 65, 65, 67, 50, 100, 90, 80, 60, 82, 85.  Percent or relative frequency distribution table Educational status of 750 workers in Iron and Steel industry, Egypt 2020 Education No. of workers Percent Illiterate 72 9.6 Read and write 150 20.0 Primary level 270 36.0 Preparatory level 180 24.0 Secondary level 60 8.0 High and university 18 2.4 Total 750 100.0  Cumulative frequency distribution table a cumulative frequency is defined as the total of frequencies, that are distributed over different class intervals. It shows the total number of observations either less or more than a given level of variable to get either ascending or descending distribution. Cumulative frequency distribution table Weight in Kg Frequency Percent (relative frequency) Cum. Relative frequency 50 – 60 (kg) 1 8.3 1 60 – 70 (kg) 4 33.3 5 70 – 80 (kg) 0 zero 5 80 – 90 (kg) 4 33.3 9 90- 100 (kg) 3 25 12 Total 12 100.0 Cumulative frequency distribution table  Question: Build a cumulative frequency distribution table for the following data, using 7 classes: 1, 6, 9, 11, 12, 13, 14, 21, 21, 23, 26, 27, 28, 29, 29, 31, 31, 32, 33, 34, 35, 36 Class Frequency 0- 5 1 6- 10 2 11-15 4 16-20 0 21-25 3 26-30 5 31-35 6 Class Frequency Cumulative frequency 0- 5 1 1 6- 10 2 3 11-15 4 7 16-20 0 7 21-25 3 10 26-30 5 15 31-35 6 21  Complex tables Male Female Total Weight in Kg Frequency Percent Frequency Percent Frequency Percent 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) 90- 100 (kg) Total 2 X 2 table Smoking status Lung cancer Total Positive Negative Smokers 8 6 14 Non smokers 2 4 6 Total 10 10 20 Graphical Presentation/ illustrations Statistical data are presented in the form of graphs, charts, and other illustrations for easier and clear understanding of their meaning, just a look. Types of graphs: Quantitative Data: 1. line graphs 2. Histogram 3. Frequency polygon Qualitative Data: 1. Bar chart ( simple, component, complex) 2. Pie chart 3. Pictogram  Line graph A line graph is particularly useful when we want to show the trend of a variable over time. Time is displayed on the horizontal axis (x-axis) and the variable is displayed on the vertical axis (y- axis).  Continuous Histogram quantitative Data A histogram is a visual representation of the distribution of quantitative data. The observations of a frequency distribution table are presented as rectangles (columns). The rectangles are drawn side by side (without spaces in between as in bars) to get a block diagram called “ histogram”  Frequency polygon Continuous quantitative After drawing the histogram which represents the Data frequency distribution of a particular characteristic, the mid-points of the upper bases of the rectangles are connected together by straight lines to get the frequency polygon (frequency curve) The curve shows the general pattern of the represented characteristic. Example : In a batch of 400 students, the height of students are represented through a frequency polygon.  Qualitative data Bar charts Types of bar charts: 1. Simple bar chart 2. Complex/ Multiple bar chart 3. Component bar chart  Simple bar chart Example : Favorite colour among group of children Vertical bar chart  Simple bar chart Horizontal bar chart  Multiple/ complex bar chart In this example, we are still looking at the popularity of different colours (our categories), but have also grouped them into broad age groups determined by their stage of schooling.  Multiple/ complex bar chart In this example, we are still looking at the popularity of different colours (our categories), but have also grouped them into broad age groups determined by their stage of schooling.  Qualitative data Pie chart A pie chart is used to display a set of categorical data. It is a circle, which is divided into segments. Each segment represents a particular category. The area of each segment is proportional to the number of cases in that category. Favorite games among medical students Football Swimming Basketball Hockey Total 15 25 10 10 50 30% 50% 20% 20% 100% 108 180 72 72 360 Hockey Football 17% 25% Basketball 16% Football Swimming Swimming 42% Basketball Hockey  Pictographs Pictographs are charts that are used to represent data using icons and images relevant to the data. A key is often included in a pictograph that indicates what each icon or image represents. Example: A survey of 40 children to ask about favorable different flavors of pizza they are like Quiz 1 Which of the following charts is most effective for displaying trends over time? A) Pie chart B) Line graph C) Bar chart D) Histogram Quiz 2 Which method is best for showing the distribution of a continuous variable? A) Pie chart B) Bar chart C) Histogram D) Table Quiz 3 A circular chart divided into sectors, where each sector represents a proportion of the whole, is called: A) Line graph B) Histogram C) Pie chart D) Scatter plot Thank you