ppt of excel

1. Data Visualization Using Microsoft Excel
Dr. Jia Uddin
AI and Big Data Department
Endicott College, Woosong University
Daejeon, South Korea
Email: jia.Uddin@wsu.ac.kr
https://sites.google.com/view/drjiauddin/home?authuser=2

2. Common general types of data visualization
Charts (Bar, Line, Pie, Scatter)
Tables
Graphs
Maps
Infographics
Dashboards

3. Common general types of data visualization
Charts
• Bar Chart

4. Common general types of data visualization
Charts
• 2D line Chart

5. Charts
• Pie Chart

6. Charts
• Scatter
(Bubble) Chart

7. Common general types of data visualization
Charts (Bar, Line, Pie, Scatter)
Tables
Graphs
Maps
Infographics
Dashboards

8. Tables

9. Tables vs Chart
Table Chart

10. Table vs Frequency

11. Normal distribution

12. Positive skew distribution

13. Negative skew distribution

14. Positive skewed distribution

15. skewed distributions

16. Measure skewness

17. Measure kurtosis
• How spread the dataset
• +ve kurtosis means too many data in the tails and not enough in
center
• -ve kurtosis means too few data are in the tails
Positive kurtosis indicates a relatively peaked distribution.
Negative kurtosis indicates a relatively flat distribution.

18. Measure kurtosis

19. Measure kurtosis

20. Correlations

21. Correlations

22. Correlations

23. Correlations
Close to 1 is strongly correlated
Close to 0 is no relation

24. Correlations

25. Correlations

26. Correlations

27. Regression

28. Regression

29. Regressions

30. Regressions
R-squared measures the strength of the relationship between your model and
the dependent variable on a convenient 0 – 100% scale

31. Time Series Plot

32. Time Series Plot
• Pivot Chart

33. Quartile and Interquartile Range

34. Interquartile Range

35. Constructing Histograms and Bar Graphs from
Raw Data
1
2
3

36. Box-plot
• another way of representing a data set graphically
• It is constructed using the quartiles, and gives a good indication of the
spread of the data set and its symmetry
• It is a very useful method for comparing two or more data sets
• The box-plot consists of a scale, a box drawn between the first and
third quartile, the median placed within the box, whiskers on both
sides of the box and outliers (if any)
Make Box and Whisker Plots
https://www.youtube.com/watch?v=mhaGAaL6Abw

37. Constructing a Box-plot
Now we calculate the median, the first quartile and the third
quartile.
For these data, median = 54, the first quartile = 50.5 and the
third quartile = 58.
With this information we can begin to construct the box-plot.

39.  The marks from all years are left-skewed, but those from 1996
and 1997 quite markedly so.
 1996 had the highest median score but the least spread. The
marks from 1998 vary more than those in 1996 and 1997.
 In all years, over 75% of students passed the course.
Comparing Data Sets Using Box and Whisker Plots
https://www.youtube.com/watch?v=U0NZu6f5TMI
https://www.youtube.com/watch?v=e79pyv5mfek

40. Measures of Central Tendency

41. Measures of Dispersion

42. Standard Deviation and Variance

43. Histogram

44. Data visualization using Infographic
https://www.worldometers.info/coronavirus/#countries

45. Dashboard

46. Data Visualization using Map