Answer:
Check the explanation
Step-by-step explanation:
Here we have to first of all carry out dependent sample t test. consequently wore goggles first was selected at random for the reason that the reaction time in an emergency taken with goggles would be greater than the amount of reaction time in an emergency taken with not so weakened vision. So that we will get the positive differences d = impaired - normal
b)
To find 95% confidence interval first we need to find sample mean and sample sd for difference d = impaired minus normal.
We can find it using excel that is in the first attached image below,
Therefore sample mean
= 0.98
Sample sd
= 0.3788
To find 95% Confidence interval we can use TI-84 calculator,
Press STAT ----> Scroll to TESTS ---- > Scroll down to 8: T Interval and hit enter.
Kindly check the attached image below.
Therefore we are 95% confident that mean difference in braking time with impaired vision and normal vision is between ( 0.6888 , 1.2712)
Conclusion : As both values in the interval are greater than 0 , mean difference impaired minus normal is not equal to 0
There is significant evidence that there is a difference in braking time with impaired vision and normal vision at 95% confidence level .
The y intercept is at 2 and the x intercept is at 3
Answer:
C would be equal to (f - 13)/(10 - d)
Step-by-step explanation:
In order to find this, you must manipulate the equation so that the left side has every term with a c in it. Then you can isolate it by dividing and find what it is equal to.
10c - f = -13 + cd -----> Add f to both sides
10c = f - 13 + cd -----> Subtract cd from both sides
10c - cd = f - 13 ------> Pull out c
c(10 - d) = f - 13 -----> Divide by (10 - d)
c = (f - 13)/(10 - d)
Answer + Step-by-step explanation:
(a)
Check the attached image.
(b)
Range of sample means : 7.5 - 5.75 = 1.25
(c)
The closer the range of the sample means is to 0 ,
the more confident they can be in their estimate . 
The farther the range of the sample means is from 0 ,
the more confident they can be in their estimate .
The mean of the sample means will tend to be a better estimate
than a single sample mean . 
A single sample mean will tend to be a better estimate
than the mean of the sample means .
Answer:
Hi
Step-by-step explanation: