- This topic has 1 reply, 1 voice, and was last updated 9 years ago by .
You must be logged in to reply to this topic.
Viewing 2 posts - 1 through 2 (of 2 total)
You must be logged in to reply to this topic.
You must be logged in to reply to this topic.
Here is your 2nd HW assignment, which will be due Monday Sept 30. As before, you can choose to do either the WebWork set or the exercises from the textbook (or do both for extra practice and extra credit):
WebWork (http://mathww.citytech.cuny.edu/webwork2/MAT1272-Ganguli): “Assignment2_-_Sec_2.3-2.4”
Textbook:
Sec 2.3: 19, 21, 25, 29
Sec 2.4: 1, 11, 13, 25, 27
The WebWork set includes a few questions which ask you to calculate z-scores. I had been planning on covering this on Wednesday, since it’s covered in Sec 2.5 of the textbook.
I will go over it tomorrow in class, so I will extend the due date on the homework to Wednesday (for both WebWork and textbook HW)
But you can go ahead and compute z-scores. The formula for the z-score of a data value x is:
z = (x- μ) / sigma
where μ is the mean and σ is the standard deviation. See p105 of the textbook.
Via http://en.wikipedia.org/wiki/Standard_score (the z-score is also called standard score):
“In statistics, the standard score is the (signed) number of standard deviations an observation or datum is above the mean. Thus, a positive standard score represents a datum above the mean, while a negative standard score represents a datum below the mean. It is a dimensionless quantity obtained by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation. This conversion process is called standardizing or normalizing “
You must be logged in to reply to this topic.
Ursula C. Schwerin Library
New York City College of Technology, C.U.N.Y
300 Jay Street, Library Building - 4th Floor
Our goal is to make the OpenLab accessible for all users.