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9a. Charts

CSCI N207 Data Analysis Using Spreadsheet. 9a. Charts. Lingma Acheson linglu@iupui.edu. Department of Computer and Information Science, IUPUI. Purpose of Charts. Provide a pictorial representation of your data Help understand data better E.g. N207 Spring Grades. Purpose of Charts.

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9a. Charts

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  1. CSCI N207 Data Analysis Using Spreadsheet 9a. Charts Lingma Acheson linglu@iupui.edu Department of Computer and Information Science, IUPUI

  2. Purpose of Charts • Provide a pictorial representation of your data • Help understand data better • E.g. N207 Spring Grades

  3. Purpose of Charts E.g. Percentage of movie rentals:

  4. Purpose of Charts • Caution! • Charts can be misleading, unfair or exaggerating! • E.g. distortion.xlsx

  5. Common Chart Elements • All charts have some elements in common, including: • Data Range • X & Y Axes • Upper & Lower Bounds • Labels • Graph Type

  6. Data Range • Generally, you will create a spreadsheet that holds or generates data, then use the graph to illustrate the data. • You will select the data you want from a spreadsheet, e.g. B2:B25

  7. X and Y Axes • The X axis is the horizontal border of the chart. • The Y axis is the vertical border. • If the graph looks completely wrong, might need to change the X - Y orientation. • Normally you need labels to describe each axis.

  8. Upper and Lower Bounds • Need to specify the upper and lower limits of the axes. • The program will usually try to guess what you want, but you may still need to modify it. • You need to be careful changing the lower bound of a graph as it can drastically distort your data. • Your upper bound should be no larger than it needs to be.

  9. Labels • There will usually be an option for setting or changing the labels on a graph. • You should use this judiciously. • Only use labels if they give necessary information, but remove them if they do not add value. • The most important part of the graph is the pictorial representation of the data. Unneeded labels decrease the size of the picture.

  10. Types of Data Analysis • Univariate analysis • describe and explain the characteristics of a single variable(one data field) • E.g. What is the average grade? How many are above 90? • Multivariate analysis • describe and explain the characteristics of multiple variables (e.g., two data fields) • Purpose: find correlation between multiple variables • E.g. What’s the correlation between grade performance and job situation? • Caution: When sorting, sort with expansion so that the relationship between two data items in each row is maintained.

  11. Chart Types • Need to determine what type of graph best describes your analysis • The chart type should be chosen carefully and is dependent on the data to be displayed.

  12. Excel Chart Types

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