Answer:
- 0.964
Step-by-step explanation:
Given that Coefficient of determination (R^2) = 0.93
Slope of regression line = - 5.26
The linear correlation Coefficient =?
The Coefficient of determination (R^2) is used to obtain the proportion of explained variance of the regression line. It is the square of the linear correlation Coefficient (R).
Hence. To obtain the linear correlation Coefficient (R) from the Coefficient of determination (R^2); we take the square root of R^2
Therefore,
R = √R^2
R = √0.93
R = 0.9643650
R = 0.964
However, since the value of the slope is negative, this depicts a negative relationship between the variables, hence R will also be negative ;
Therefore, R = - 0.964
Answer:
False
Step-by-step explanation:
The sequence seems to be increasing by 3+3(-5+3=-2, -2+3+3=4, so on). By 13, the sequence is increasing by 11, making the next number 24.
Answer:
1.600
dont forget to press the crown:)
Step-by-step explanation:
We have the equation:
8 ÷ 5 = 1.600
Calculated to 3 decimal places.
1. 6 0 0
5 8. 0 0 0
− 5
3 0
− 3 0
0 0
− 0
0 0
− 0
0
Answer: (3,inf)
(-inf,3)
Step-by-step explanation:
Sample mean : \overline{x}=10.6x=10.6
Standard deviation : s=1.7s=1.7
Significance level : \alpha:1-0.95=0.05α:1−0.95=0.05
Critical value : z_{\alpha/2}=1.96
Hence the 95% confidence interval for the number of chocolate chips per cookie for big chip cookies= (10.1989,\ 11.0011)(10.1989, 11.0011)
