Answer:
a.) 1/3
Step-by-step explanation:
1/6 is a 2 is rolled
1/6 if a 4 is rolled
so 2/6 if either are rolled
which simplifies to 1/3
Answer:
Probability of a dice rolling a number less than 3 is 2/6 = 1/3
Probability of dice spinning a number less than 6 is 5/6
Step-by-step explanation:
Number less than 3:
Chances of no. Being 1 and 2, not including 3, is 1/6 individually.
Hence, chances of no. Rolled being lesser than 3 is 1/6 + 1/6 = 1/3
Probability of no. Being smaller than 6 (lesser than 6) Aka spinning 1 or 2 or 3 or 4 or 5, not including 6 is (1/6) x 5 = 5/6
Step-by-step explanation:
5. Let the equation of the line be y = mx + c
m = (6-15)/(2-(-1)) = -3
sub (2, 6) and m = -3:
6 = -3(2) + c
c = 12
Equation of the line: y = -3x + 12
6. Let the equation of the line be y = mx + c
y-intercept of 7 means c = 7
y = mx + 7
x-intercept: value of x when y = 0
therefore, sub (4, 0):
0 = m(4) + 7
m = -7/4
Equation of the line: y = -7/4x + 7
this is a topic on coordinate geometry. If you wish to explore more into this topic you can give me a follow on Instagram (learntionary) I'll be posting the notes for this topic soon and will also be posting other topics' notes and some tips :)
Answer:
B. The coefficient of determination is 54.76%. Therefore, 54.76% of the variation in weight can be explained by the regression line.
Step-by-step explanation:
The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.
The coefficient of determination is a measure to quantify how a model explains an dependent variable.
The formula for the correlation coeffcient is given by:
![r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%28%5Csum%20xy%29-%28%5Csum%20x%29%28%5Csum%20y%29%7D%7B%5Csqrt%7B%5Bn%5Csum%20x%5E2%20-%28%5Csum%20x%29%5E2%5D%5Bn%5Csum%20y%5E2%20-%28%5Csum%20y%29%5E2%5D%7D%7D)
The formula for the coefficient of determination is 
In our case the correlation coefficient obtained was 0.74
And the determination coefficient is
, and if we convert this into % we got 54.76%
Assume that height is the predictor (X) and weight is the response (Y)
And the best answer for this case is:
B. The coefficient of determination is 54.76%. Therefore, 54.76% of the variation in weight can be explained by the regression line.
Answer:
y=1, y=-2/5
Step-by-step explanation: