Answer:A. provide evidence of a causal relationship between an independent variable and the variable to be forecast
Step-by-step explanation: Casual model tends to show the cause and effect relationship between the dependent variable to be forcasted and the independent variables upon which the dependent variable is dependent.
Casual model is frequently used in the field of Statistics and Economics when making forcasts about future investments or the cause of certain events,knowing what activities to carry out in the future.
Answer is 432 cans in total
18 packs times 24 cans in each is 432
Answer: v=-81.92
Step-by-step explanation:
Multiply both parts of the equation by 8:
Answer:
B. 0.602%
Step-by-step explanation:
Probability is essentially (# times specific event will occur) / (# times general event will occur). Here, we have a few specific events: draw a quarter, draw a second quarter, draw a penny, and draw another penny. The general event will just be the number of coins there are to choose from.
The probability that the first draw is a quarter will be 4 / (4 + 8 + 9) = 4/21.
Since we've drawn one now, there's only 21 - 1 = 20 total coins left. The probability of drawing a second quarter is: (4 - 1) / (21 - 1) = 3/20.
The probability of drawing a penny is: 9 / (20 - 1) = 9/19.
The probability of drawing a second penny is: (9 - 1) / (19 - 1) = 8/18.
Multiply these four probabilities together:
(4/21) * (3/20) * (9/19) * (8/18) = 864 / 143640 ≈ 0.602%
The answer is B.
Answer:
1/2x+3
Step-by-step explanation:
I graphed it
