Answer:
the third one
Step-by-step explanation:
HOPE THIS HELPS!!!!
Incorrect: 0.3 is equivalent to 3/10.
0.03 is equivalent to 3/100
All of them are except for number 1
For the experiment, you need 2L of cola. Your first option would be to purchase 1 2L bottle of cola for $2.25.
To calculate the second option, let's convert milliliters to liters first. There are 1,000 milliliters in 1 liter. With this, we know that there are 2,000 milliliters in 2 liters. Option 2 comes in 500-milliliter cans, which means that you would need 4 of them (2,000/500 = 4). 4 cans multiplied by $0.50 would cost you $2.00.
Let's check the cost of your answer options.
A. 4 cans - As seen above, this would cost $2.00.
B. 1 bottle - From the question, we know this would cost $2.25.
C. 2 bottles - This would be more soda than you need and would cost $4.50 ($2.25x2)
D. 1 can - This would be .5L and not enough soda for the experiment.
E. 5 cans - This would cost $2.50, but would be an extra 500mL of soda.
F. 2 cans - This would only be 1L of soda and not enough for the experiment.
G. 3 cans - This would be 1.5L of soda and not enough for the experiment either.
For the best price option, you would choose A (four cans of soda). This would give you the amount of soda that you need at the lowest price.
Answer:
True.
Step-by-step explanation:
A probability distribution is a listing of all the outcomes of an experiment and the probability associated with each outcome. Probability distribution is associated with the following characteristics or properties;
1. The outcomes are mutually exclusive.
2. The list of outcomes is exhaustive, which simply means that the sum of all probabilities of the outcomes must equal one (1).
3. The probability for a particular value or outcome must be between 0 and 1.
Since a probability distribution gives the likelihood of an outcome or event, a single random variable is divided into two main categories, namely;
I. Probability density functions for continuous variables.
II. Discrete probability distributions for discrete variables.
For example, when a coin is tossed, you can only have a head or tail (H or T).
Also, when you throw a die, the only possible outcome is 1/6 and the total probability for it all must equal to one (1).
