Answer:
The rigid transformation, which does not change the shape or size of the preimage. The non-rigid transformation, which will change the size but not the shape of the preimage.
Step-by-step explanation:
Answer:
The slope of the perpendicular line to the line is
m = 
Step-by-step explanation:
<u><em>Step(i):-</em></u>
Given that the line y =f(x) = 2x +6
⇒ y = 2x +6
comparing y =mx +c
The slope of the given line m =2
<u><em>Step(ii):- </em></u>
The slope of the perpendicular line = 
The slope of the perpendicular line =
Answer:
The Answer is c
Step-by-step explanation:
Answer: There is a strong positive correlation between number of games won by a minor league baseball team and the average attendance at their home games is analyzed.
Step-by-step explanation:
The Pearson's coefficient 'r' gives the correlation between the predicted values and the observed values .
- It tells the direction and the strength of the relation.
- When r is negative it means there is a negative relationship between the variables .
- When r is positive it means there is a positive relationship between the variables .
- When |r|=1 , strong correlation ,
- When r=0 , there is no correlation.
- If 0.70<|r|<1 , there is a strong correlation.
- If 0.50<|r|<0.70 , there is a moderate correlation.
- If 0.30<|r|<0.50 , there is a low correlation.
Given : A regression to predict the average attendance from the number of games won has an r = 0.73.
Since r=0.73 is positive and 0.70 <0.73 <1 , it means there is a strong positive correlation between number of games won by a minor league baseball team and the average attendance at their home games is analyzed.
