Answer:
The predicted calories would be 403 calories.
Step-by-step explanation:
We have a linear regression model relating y: calories with x: carbohydrates, which has a slope of 4.0 and a y-intercept of 3.0.
Then, the model equation is:
With these model we can predict the calories values for any amount of carbohydrates, within the interval within which this model is valid.
If a new food is tested, and the number of carbohydrates (x) is 100, the predicted value will be:
The predicted calories would be 403 calories.
Answer: Our required probability is 0.83.
Step-by-step explanation:
Since we have given that
Number of dices = 2
Number of fair dice = 1
Probability of getting a fair dice P(E₁) = 
Number of unfair dice = 1
Probability of getting a unfair dice P(E₂) =
Probability of getting a 3 for the fair dice P(A|E₁)= 
Probability of getting a 3 for the unfair dice P(A|E₂) = 
So, we need to find the probability that the die he rolled is fair given that the outcome is 3.
So, we will use "Bayes theorem":
Hence, our required probability is 0.83.
Answer:
42
Step-by-step explanation:
i said so
2.41667, you can also find a converter online.
Answer:
1.1x
Step-by-step explanation:
that is the procedure above
