ENT 526 Chapter Notes - Chapter 2: Scatter Plot, Bar Chart
4 May 2018
School
Department
Course
Professor
Nov 17 – logic
Youe got data, no hat?
- Select the categories in which the raw data can be summarized
- Code the data (sort into categories)
- Present the data in a form that helps you to draw conclusions
Categories
- First step in summarizing and presenting data is to construct tables, graphs, or charts
- But before you can do that, need to categorize the data
- One way of doing this is to look at some of the extreme observations and averages
- This gives you a point for comparison
- You could also separate based on strata of observation
- Once you select categories, you reclassify your raw data into the more inclusive categories
- After completing this step, you are now ready to present your research in a table
Tables –sex education in public schools
- In order to put the appropriate numbers in your table, you need to cross-tabulate your data
- In the aforementioned chi-square table, you should have all your sample contained within the table
- The numbers at the right hand, and bottom of the table are known as marginal totals
- If they dont add up properly, your data ill not e aurately aptured
- Numbers in tables can be demonstrated by both whole numbers, or raw counts, or percentages. When creating
comparisons with different marginal totals, it might be best to use percentages over the whole number
- Also, it is important to keep in mind the relationship between IV and DV here to interpret the results correctly
Bar Graph
- Bar graph or histograms show variation through the amount of space that one bar (or aspect of a variable) take
up
Pie graph
- Are appropriate when analysis examines the proportion of variable categories to all variable categories over the
whole population
- Eah group oupies a edge proportion of the total area of the pie graph. This is alulated by multiplying the
percentage by 360 to find the amount of degrees that a wedge should occupy
- Look nice, but the differences can sometimes be hard to compare among groups
Scattergrams
- Pinpoint each instance of measurement on a grid defined by two axes of a graph
- Need to decide on the scale of units to be used on each axis
- No need to categorize and code data here
- The extremes of your data will form the scale of units
- Each dot on the scattergram represents an intersection among the two variables and consequently two
measurements at the same time.
Line graphs
- Almost the same as a scattergram, but has a line connecting consecutive data points
- When you have two dots at the same vertical point, calculate the average and put a line through the empty
space
- Watch out for the troll line graphs
Means
- Calculating averages in order to compare groups
- However, when you use means you lose all variation internal to each group
- Averages are also highly affected by outliers
Quick summary
- Scattergram – presents most information
- Line, bar, and pie graphs – less info
- Means – least info
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Select the categories in which the raw data can be summarized. Present the data in a form that helps you to draw conclusions. First step in summarizing and presenting data is to construct tables, graphs, or charts. But before you can do that, need to categorize the data. One way of doing this is to look at some of the extreme observations and averages. Once you select categories, you reclassify your raw data into the more inclusive categories. After completing this step, you are now ready to present your research in a table. You could also separate based on strata of observation. In order to put the appropriate numbers in your table, you need to cross-tabulate your data. In the aforementioned chi-square table, you should have all your sample contained within the table. The numbers at the right hand, and bottom of the table are known as marginal totals.
