When a scientist conducted a genetics experiments with peas, one sample of offspring consisted of 917 peas, with 719 of them having red flowers. If we assume, as the scientist did, that under these circumstances, there is a 3/4 probability that a pea will have a red flower, we would expect that 687.75 (or about 688) of the peas would have red flowers, so the result of 719 peas with red flowers is more than expected. a. If the scientist's assumed probability is correct, find the probability of getting 719 or more peas with red flowers. b. Is 719 peas with red flowers significantly high? c. What do these results suggest about the scientist's assumption that 3/ 4 of peas will have red flowers? a. If the scientist's assumed probability is correct, the probability of getting 719 or more peas with red flowers is (Round to four decimal places as needed.) CALCULUS b. Is 719 peas with red flowers significantly high? because the probability of this event is than the probability cutoff that corresponds to a significant event, which is c. What do these results suggest about the scientist's assumption that 3/4 of peas will have red flowers? A. Since the result of 719 peas with red flowers is not significantly high, it is not strong evidence against the scientist's assumption that 3/4 of peas will have red flowers. B. Since the result of 719 peas with red flowers is significantly high, it is not strong evidence against the scientist's assumption that 3/4 of peas will have red flowers. C. Since the result of 719 peas with red flowers is significantly high, it is strong evidence supporting the scientist's assumption that 3/4 of peas will have red flowers. O D. The results do not indicate anything about the scientist's assumption. E. Since the result of 719 peas with red flowers is not significantly high, it is strong evidence against the scientist's assumption that 3/4 of peas will have red flowers. F. Since the result of 719 peas with red flowers is significantly high, it is strong evidence against the scientist's assumption that 3/4 of peas will have red flowers.
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
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