Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

GrC 320 Histograms

A brief presentation for Graphic Communication 320 on Histograms.
by

Alyssa Pelletier

on 26 April 2010

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of GrC 320 Histograms

HISTOGRAMS A representation of
a frequency distribution by means of rectangles whose widths represent class intervals and whose areas are proportional to the corresponding frequencies Allow us to aggregate and sort variable data into (usually) equal sized bins to allow quick evaluation of large data sets 2. Determine the bin width, "H"
{H = R / K}

In this case, H = 8 / 9 = .88 Determine the starting boundary
{Min Value - 1/2 H}

In this case, 1 - .44 = .66 Make sure each bin is mutually exclusive & each data point fits into only one. Construct a histogram using the frequency table. This means that
Bin 1 is from . 66 to 1.54
Bin 2 is from 1.55 to 2.42
Bin 3 is from 2.43 to 3.31
etc...
3.
Interpreting
Histograms 1. Count the number of data points.
In this case, there are 25. Start with an unorganized set of numbers.
1, 9, 2, 8, 6, 8, 3, 7, 3, 7,
3, 5, 4, 6, 5, 2, 4, 6, 4, 6,
5, 5, 7, 5, 4 Determine the range "R"for the data set.
{R = Max Value - Min Value.}

In this case, R = 9 - 1 = 8 Divide the data set into a certain number of bins, "K"

In this case, we have less
than 50 data points, so we should use
5 -7 bins. However, our data is nice, so we're going to use 9. Creating Histograms
Full transcript