Each table shows a proportional relatioship. fill in the missing values and determine k.

Mathematics

1 answer:

kolbaska11 [484]2 years ago

8 0

Answer:

what table ..............there is no table

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At a college the scores on the chemistry final exam are approximately normally distributed, with a mean of 75 and a standard dev

AysviL [449]

Answer:

b) Chemistry

Step-by-step explanation:

To compare both scored we need to standardize the scores using the following equation:

$\frac{x-m}{s}$

Where x is the score, m is the mean and s is the standard deviation. So, 82 on chemistry is equivalent to:

$\frac{82-75}{15}=0.4667$

Because the mean of the scores on the chemistry final exam is equal to 75 and the standard deviation is 15

At the same way, 80 on Calculus is equivalent to:

$\frac{80-83}{13} =-0.2308$

Because the mean of the scores on the calculus final exam is equal to 83 and the standard deviation is 13

Now, we can compare the values. So, taking into account that -0.2308 is lower than 0.4667, we can said that the student do better in Chemistry.

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2 years ago

The number of bank robberies that occur in Lagos is modeled to be Poisson distributed with mean of 1.8 per day. Find the probabi

cupoosta [38]

The Poisson distribution is a discrete distribution that calculates the likelihood that a certain number of events will occur within a certain amount of time.

The probability of getting exactly three robberies in a day is 0.1607.

<h3>What is meant by poison distribution?</h3>

The Poisson distribution is a discrete probability distribution used in probability theory and statistics to express the likelihood that a given number of events will occur within a specified time or space interval if they occur at a known constant mean rate and regardless of the interval since the last event.

The Poisson distribution is a discrete distribution that calculates the likelihood that a certain number of events will occur within a certain amount of time.

In the poison distribution a discrete random variable X has the following probability mass function,

$P(X=x)=\frac{e^{-\lambda} \cdot \lambda^x}{x !}$ , where $\lambda$ is the mean of the distribution and $x=0,1,2,3 \ldots \ldots$