Answer:
0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
Given the data in the question;
sample size n = 28
slope of the least squares regression line of y on x or sample estimate = 0.0623
standard error = 0.0224
95% confidence interval
level of significance ∝ = 1 - 95% = 1 - 0.95 = 0.05
degree of freedom df = n - 2 = 28 - 2 = 26
∴ the equation will be;
⇒ sample estimate ± ( t-test) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
⇒ sample estimate ± ( 
) ( standard error )
{ from t table; ( ) = 2.055529 = 2.056
so we substitute
⇒ 0.0623 ± ( 2.056 )( 0.0224 )
Therefore, 0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Answer:
Step-by-step explanation:
We will use 2 coordinates from the table along with the standard form for an exponential function to write the equation that models that data. The standard form for an exponential function is
where x and y are coordinates from the table, a is the initial value, and b is the growth/decay rate. I will use the first 2 coordinates from the table: (0, 3) and (1, 1.5)
Solving first for a:
. Sine anything in the world raised to a power of 0 is 1, we can determine that
a = 3. Using that value along with the x and y from the second coordinate I chose, I can then solve for b:
. Since b to the first is just b:
1.5 = 3b so
b = .5
Filling in our model:
Since the value for b is greater than 0 but less than 1 (in other words a fraction smaller than 1), this table represents a decay function.
Answer:
A. 77 kilometers per hour
Step-by-step explanation:
Speeds of vehicles are normally calculated in kilometers per hour, meters per hour is too small the measurement and millimeters is even smaller.
Answer: Quedarían nueve
Step-by-step explanation:
