Test: Probability - JSS 2 MCQ

The even numbers on a die are 2, 4, and 6, making 3 favorable outcomes. Since there are 6 total outcomes, the probability of rolling an even number is P(even) = 3/6 = 1/2.

When tossing a coin, there are two possible outcomes: heads (H) or tails (T). Thus, the total number of outcomes is 2, making it a simple binary random experiment.

A probability of 0 indicates that the event is impossible. This means that under the defined conditions of the experiment, the event cannot occur at all.

All numbers on the die (1, 2, 3, 4, 5, 6) are less than 7, making all 6 outcomes favorable. Therefore, the probability P(number < 7)="6/6" =="" 1,="" indicating="">

An event in probability refers to a specific outcome or a set of outcomes from a sample space. For instance, obtaining heads in a coin toss is one such event.

There are 6 doublets possible when rolling two dice: (1,1), (2,2), (3,3), (4,4), (5,5), and (6,6). The total number of outcomes when rolling two dice is 36 (6x6), so the probability of rolling a doublet is 6/36 = 1/6.

Tossing a coin is classified as a random experiment because all possible outcomes are known (heads or tails), but the exact outcome cannot be predicted ahead of time.

When flipping a coin, there are 2 possible outcomes (H and T) and only 1 favorable outcome (H). Thus, the probability of getting heads is P(H) = 1/2.

As the number of trials increases, the experimental probability tends to get closer to the theoretical probability. This is because more data points provide a better representation of true likelihood.

Probability values are always between 0 and 1, where 0 indicates an impossible event and 1 indicates a certain event. This range helps in quantifying the likelihood of various outcomes accurately.

The sample space is defined as the set of all possible outcomes of a random experiment. For instance, when flipping a coin, the sample space is {H, T}.

A trial refers to each repetition of a random experiment. For example, flipping a coin once is one trial, and repeating this process multiple times constitutes multiple trials.

Experimental probability can differ from theoretical probability due to a small sample size or random variation in trials. As more trials are conducted, the experimental probability typically approaches the theoretical probability.

The experimental probability is calculated by taking the number of times heads occurred (7) and dividing it by the total number of trials (10). Therefore, the experimental probability of heads is P(H) = 7/10.

The favorable outcome for obtaining tails when flipping a coin is T (tails). Since there are only two possible outcomes, heads (H) and tails (T), the outcome of tails is specifically what we are considering favorable.

The numbers greater than 4 on a die are 5 and 6. Thus, there are 2 favorable outcomes. Since the total number of outcomes is 6, the probability P(number > 4) = 2/6 = 1/3.

The probability of an event is calculated using the formula P(E) = (Number of favorable outcomes) / (Total number of possible outcomes). This means we divide the number of outcomes that are favorable to the event by the total outcomes possible in the experiment.

The prime numbers on a die are 2, 3, and 5. This gives us 3 favorable outcomes. Since there are 6 total outcomes, the probability P(prime) = 3/6 = 1/2.

Experimental probability is calculated based on the actual results of trials, while theoretical probability is based on the expected outcomes assuming perfect conditions. They may differ, especially with a small number of trials.

An impossible event is one that cannot occur. In the case of rolling a standard die, getting a 7 is impossible because the die only has faces numbered from 1 to 6.