Answer:
P(X>4)= 0.624
Step-by-step explanation:
Given that
n = 10
p= 0.5 ,q= 1 - p = 0.5
Two fifth of 10 = 2/5 x 10 =4
It means that we have to find probability P(X>4).
P(X>4)= 1 -P(X=0)-P(X=1)-P(X=2)-P(X=3)-P(X=4)
We know that
P(X>4)= 1 -P(X=0)-P(X=1)-P(X=2)-P(X=3)-P(X=4)
P(X>4)= 1 -0.0009 - 0.0097 - 0.043 - 0.117-0.205
P(X>4)= 0.624
The answer is 140.
For every 4 toys the price increases by 20. If you divide, we find that every toy is worth 5. For example, if the amount of toys increases by 10, then the cost increases by 50. Since 20 is the closest given example being only 10 toys away, you can just add 50 onto the cost of the toys to get 140.
Answer:
a) y = 0.74x + 18.99; b) 80; c) r = 0.92, r² = 0.85; r² tells us that 85% of the variance in the dependent variable, the final average, is predictable from the independent variable, the first test score.
Step-by-step explanation:
For part a,
We first plot the data using a graphing calculator. We then run a linear regression on the data.
In the form y = ax + b, we get an a value that rounds to 0.74 and a b value that rounds to 18.99. This gives us the equation
y = 0.74x + 18.99.
For part b,
To find the final average of a student who made an 83 on the first test, we substitute 83 in place of x in our regression equation:
y = 0.74(83) + 18.99
y = 61.42 + 18.99 = 80.41
Rounded to the nearest percent, this is 80.
For part c,
The value of r is 0.92. This tells us that the line is a 92% fit for the data.
The value of r² is 0.85. This is the coefficient of determination; it tells us how much of the dependent variable can be predicted from the independent variable.
