3.345 becuase 3.3 could be 3.30 and the 5 can round the 4 up
Answer:
6.9
Step-by-step explanation:
sin(52)=x
x=7sin(52)
Answer:
Step-by-step explanation:
Hello!
Given the independent variable X and the dependent variable Y (see data in attachment)
The regression equation is
^Y= b₀ + bX
Where
b₀= estimation of the y-intercept
b= estimation of the slope
The formulas to manually calculate both estimations are:


n=7
∑X= 42
∑X²= 292
∑Y= 49
∑Y²= 403
∑XY= 249




^Y= 13.75 - 1.13X
Using the raw data you can calculate the coefficient of determination as:
![R^2= \frac{b^2[sumX^2-\frac{(sumX)^2}{n} ]}{[sumY^2-\frac{(sumY)^2}{n} ]}](https://tex.z-dn.net/?f=R%5E2%3D%20%5Cfrac%7Bb%5E2%5BsumX%5E2-%5Cfrac%7B%28sumX%29%5E2%7D%7Bn%7D%20%5D%7D%7B%5BsumY%5E2-%5Cfrac%7B%28sumY%29%5E2%7D%7Bn%7D%20%5D%7D)
![R^2= \frac{(-1.13)^2[292-\frac{(42)^2}{7} ]}{[403-\frac{(49)^2}{7} ]}= 0.84](https://tex.z-dn.net/?f=R%5E2%3D%20%5Cfrac%7B%28-1.13%29%5E2%5B292-%5Cfrac%7B%2842%29%5E2%7D%7B7%7D%20%5D%7D%7B%5B403-%5Cfrac%7B%2849%29%5E2%7D%7B7%7D%20%5D%7D%3D%200.84)
This means that 84% of the variability of the dependent variable Y is explained by the response variable X under the model ^Y= 13.75 - 1.13X
I hope this helps!
Answer:
10
Step-by-step explanation:
Answer:
3.188
Step-by-step explanation:
Given that :
Sample data: 26.5, 28, 30.2, 29.6, 32.3, 24.7
Sample standard deviation (s) = 2.728
Mean (mu) = 25
Tstatistic formula :
(x - mu) / (s/sqrt(n))
n = sample size = 6 ; s = 2.728 ; mu = 25
Sample mean (x) = (26.5 + 28 + 30.2 + 29.6 + 32.3 + 24.7) / 6
Sample mean (x) = 171.3 / 6 = 28.55
Tstatistic = (28.55 - 25) / (2.728 / sqrt(6))
Tstatistic = 3.55 / 1.1137013
Tstatistic = 3.1875692