× Didn't find what you were looking for? Ask a question
Top Posters
Since Sunday
5
o
5
4
m
4
b
4
x
4
a
4
l
4
t
4
S
4
m
3
s
3
New Topic  
pretty_yas pretty_yas
wrote...
Posts: 342
Rep: 0 0
6 years ago
In a random sample of eight college women, each was asked her height (to the nearest inch) and her weight (to the nearest five pounds). A scatter diagram was constructed. From this scatter diagram, one can conclude all except for which?
  1.There is a positive linear relationship between the height and weight of the women.
  2.In general, the taller the woman the more she will weigh.
  3.Taller women must also be heavier.
  4.In general, the shorter the woman the less she will weigh.
 
Q. 2

hiCiOkU6l4PkMWIK6GttxUCwOIZ1O w7BtEc4p7hsGikODSKXSdaHOjFeTZ 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 />"

Q. 3

In a random sample of eight college women, each was asked her height (to the nearest inch) and her weight (to the nearest five pounds). The scatter diagram is shown below. What is the best estimate for r?
 
  1. r = -0.875
  2. r =0.567
  3. r = 0.865
  4. r = 0.508

Q. 4

Which is not true about the correlation coefficient?
  1.An r = 0 indicates no linear relationship between the two variables
  2.An r =1 indicates a perfect positive relationship between the two variables.
  3.The correlation coefficient must be between -1 and 1.
  4.The correlation coefficient measures the strength of the linear relationship between two qualitative variables.

Q. 5

Below is a list of ten 2005 movies with
Read 32 times
1 Reply
Replies
Answer verified by a subject expert
kiavashkiavash
wrote...
Posts: 354
Rep: 1 0
6 years ago
Sign in or Sign up in seconds to unlock everything for free
1

Related Topics

pretty_yas Author
wrote...

6 years ago
this is exactly what I needed
wrote...

Yesterday
Correct Slight Smile TY
wrote...

2 hours ago
Thank you, thank you, thank you!
New Topic      
Explore
Post your homework questions and get free online help from our incredible volunteers
  1130 People Browsing
Related Images
  
 274
  
 324
  
 688
Your Opinion
Which is the best fuel for late night cramming?
Votes: 144

Previous poll results: Where do you get your textbooks?