2614 Scatter Plot Transformations Logs
Log x and log y transformations
- 1.The log y transformation linearises the scatter plot by :
- A.
Turning the y values into log y values
- B.
Compressing the y axis values
- C.
Stretching the y axis values
- D.
Leaving the x axis values the same
- 2.The log x transformation linearises the scatter plot by :
- A.
Changing the x values to log x values
- B.
Compressing the x axis values
- C.
Stretching the x axis values
- D.
Leaving the y values as they are
- 3.
The scatter plot above will potentially be linearised with :- A.
Log x transformation
- B.
Log y transformation
- C.
It is is the wrong quadrant for these transformations
- 4.
The scatter plot above will potentially be linearised with :
- A.
Log x transformation
- B.
Log y transformation
- C.
It is is the wrong quadrant for these transformations
- 5.
The scatter plot above will potentially be linearised with :
- A.
Log x transformation
- B.
Log y transformation
- C.
It is is the wrong quadrant for these transformations
- 6.
The scatter plot above will potentially be linearised with :
- A.
Log x transformation
- B.
Log y transformation
- C.
It is is the wrong quadrant for these transformations
- 7.Which quadrants have potential for a log x transformation
- A.
Quadrant 1
- B.
Quadrant 2.
- C.
Quadrant 3
- D.
Quadrant 4
- 8.Which quadrants have potential for a log y transformation
- A.
Quadrant 1.
- B.
Quadrant 2
- C.
Quadrant 3
- D.
Quadrant 4
- 9.
The residual plot above shows the original data is potentially from which quadrants
- A.
Quadrant 1
- B.
Quadrant 2
- C.
Quadrant 3
- D.
Quadrant 4
- 10.
The residual plot above shows the original data is potentially from which quadrants
- A.
Quadrant 1
- B.
Quadrant 2
- C.
Quadrant 3
- D.
Quadrant 4
- 11.
The residual plot above shows the original data can potentially be linearised with :
- A.
Log x transformation
- B.
Log y transformation
- C.
It can't be linearised with a log transformation
- 12.
The residual plot above shows the original data can potentially be linearised with :
- A.
Log x transformation
- B.
Log y transformation
- C.
It can't be linearised with a log transformation
- 13.
The residual plot above shows the original data can potentially be linearised with :
- A.
X squared transformation
- B.
Y squared transformation
- C.
It can't be linearised with a log transformation
- 14.The log transformations are not applicable in which quadrant
- A.
Quadrant 1
- B.
Quadrant 2
- C.
Quadrant 3
- D.
Quadrant 4
- E.
They work in all quadrants.
- 15.
The image above is a transformer in Bubble Bee form from :
- A.
Quadrant 1
- B.
Quadrant 2
- C.
Quadrant 3
- D.
Quadrant 4
- E.
It wasn't funny the first time!
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