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For more information, please see full course syllabus of Statistics
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Lecture Comments (12)

0 answers

Post by Saadman Elman on August 31, 2014

It was very helpful! She clarified it very nicely.

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Post by Oliver Barry on May 2, 2014

Is there anywhere where we can get more examples to work through?

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Post by Ryan Hughes on February 10, 2014

Where does one ask questions from their class work that they would like help answering?

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Post by Abdihakim Mohamed on November 25, 2013

This is not specific, I feel like I am lost. I understand early part but the examples don't make sense. I mean basically I am lost in the examples.

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Post by Manoj Joseph on June 27, 2013

what do you mean by measured conclusions?

1 answer

Last reply by: Gayatri Arumugam
Tue Jan 8, 2013 11:48 PM

Post by Jameelah Hegazy on October 22, 2012

Great lecture.

Is it possible for members to save your lecture slides?

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Post by Matthew Manning on September 17, 2012

Just to make sure I'm understanding this correctly, Descriptive Statistics is basically exact information (the type of information that we desire from a population, but are unable to obtain. Inferential statistics is the information that we gain from samples, and we then use that info in order to come to conclusions.

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Post by Matthew Manning on September 16, 2012

What specific areas of Math on Educator.Com should I brush up on in order be successful at Statistics, I have obtained an override to bypass lower level classes. But I need to know specifically what I need to review in order to do well. Please be very specific, Thanks

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Post by Daniel Goff on April 18, 2012

great lecture...very informative

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Post by M Holland on December 1, 2010

Extra example 2 has errors in the finding the probability of the first item

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Post by Abraham Hsu on February 11, 2010

***Column "Yes" total =/= 279, but 379, therefore 178/379

Exploring Categorical Data

  • Categorical data can be summarized into a frequency table.

  • Contingency tables can be used to find marginal, conditional, and joint probabilities of events.

  • Joint probability in a contingency table is the total of the intersection of the two events divided by the total number of observations.

Exploring Categorical Data

Lecture Slides are screen-captured images of important points in the lecture. Students can download and print out these lecture slide images to do practice problems as well as take notes while watching the lecture.

  • Intro 0:00
  • Frequency Tables 0:05
    • Example: Student Age
    • Relative Frequency
  • Bar Graphs 1:59
  • Marginal and Joint Probabilities 3:54
  • Example 1: Gender and Beer 6:52
  • Conditional Probabilities 8:47
  • Example 2: Gender and Beer 11:41
  • Extra Example 1
  • Extra Example 2