Answer:
Step-by-step explanation:
<u>a)</u>
- Given that ; X ~ N ( µ = 65 , σ = 4 )
From application of normal distribution ;
- Z = ( X - µ ) / σ, Z = ( 64 - 65 ) / 4, Z = -0.25
- Z = ( 66 - 65 ) / 4, Z = 0.25
Hence, P ( -0.25 < Z < 0.25 ) = P ( 64 < X < 66 ) = P ( Z < 0.25 ) - P ( Z < -0.25 ) P ( 64 < X < 66 ) = 0.5987 - 0.4013
- P ( 64 < X < 66 ) = 0.1974
b) X ~ N ( µ = 65 , σ = 4 )
From normal distribution application ;
- Z = ( X - µ ) / ( σ / √(n)), plugging in the values,
- Z = ( 64 - 65 ) / ( 4 / √(12)) = Z = -0.866
- Z = ( 66 - 65 ) / ( 4 / √(12)) = Z = 0.866
P ( -0.87 < Z < 0.87 )
- P ( 64 < X < 66 ) = P ( Z < 0.87 ) - P ( Z < -0.87 )
- P ( 64 < X < 66 ) = 0.8068 - 0.1932
- P ( 64 < X < 66 ) = 0.6135
c) From the values gotten for (a) and (b), it is indicative that the probability in part (b) is much higher because the standard deviation is smaller for the x distribution.
Answer:
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Answer:
Step-by-step explanation:
Step 1: Identify the variables. ...
Step 2: Determine the variable range. ...
Step 3: Determine the scale of the graph. ...
Step 4: Number and label each axis and title the graph.
Step 5: Determine the data points and plot on the graph. ...
Step 6: Draw the graph.
I may be wrong but I believe that <1=<2
