Answer:
Kindly check explanation
Step-by-step explanation:
Given that :
Correlation Coefficient (r) = 0.989
alph=0.05
Number of observations (n) = 8
determine if there is a linear correlation between chest size and weight.
Yes, there exists a linear relationship between chest size and weight as the value of the correlation Coefficient exceeds the critical value.
What proportion of the variation in weight can be explained by the linear relationship between weight and chest size?
To determine the the proportion of variation in weight that can be explained by the linear regression line between weight and chest size, we need to obtain the Coefficient of determination(r^2) of the model.
r^2 = square of the correlation Coefficient
r^2 = 0.989^2 = 0.978121
Hence, about 0.978 (97.8%) of the variation in weight can be explained by the linear relationship between weight and chest size.
Answer:
2.86
Step-by-step explanation:
So I'm pretty sure we don't want the probability, just the zscore
to find the zsore subtract the mean and divide by the standard deviation
(93-87)/2.1= 2.86
the answer is 54 9/14
because Divide using long division. The whole number portion will be the number of times the denominator of the original fraction divides evenly into the numerator of the original fraction, and the fraction portion of the mixed number will be the remainder of the original fraction division over the denominator of the original fraction.
Here's a diagram showing how to combine angles LDA (in red) and angle ADE (in blue). Hopefully it becomes a bit clearer why these two angles add up to line segment LE. Erase the shared segment DA if it helps show LE better.
See attached image below.
Answer: 1 out of 6
Step-by-step explanation: A number cube has 6 numbers on it. Only one of them is a two. If she were using two number cubes then she would have 2 out of 12 chances of landing on a number 2.
