A bag contains some number of marbles. It is known that 20 of them are red. When 15 marbles are drawn, without replacement, we get 6 red. Assuming E(X)=6 red, what is the total number of marbles in the bag?

Answer:

I don't now this but you should do pemdas that really helped me

Step-by-step explanation:

The first step is perthansies  then exponents and then multiplication then division and last addition and subtraction that should give you your answer.

Answer:

a. Covariance between x and y = – 1.25

b. Correlation coefficient = – 0.07

Step-by-step explanation:

Note: This question is not complete. The complete question is therefore provided before answering the question as follows:

Consider the following sample data:

x 10 7 20 15 18

y 22 15 19 14 15

Required:

a. Calculate the covariance between the variables. (Negative value should be indicated by a minus sign. Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal place.

b. Calculate the correlation coefficient (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal place.)

The explanation to the answer is now given as follows:

Note: See the attached excel file for the calculations of the sum of x and y, means of x and y, deviations of x and y, multiplications of deviations of x and y, and others.

a. Calculate the covariance between the variables. (Negative value should be indicated by a minus sign. Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal place.)

In the attached excel file, we have:

N = Number of observations = 5

Mean of x = Sum of x / N = 70 / 5 = 14

Mean of y = Sum of y / N = 85 / 5 = 17

x - Mean of x = Deviations of x = see the attached excel file for the answer of each observation

y - Mean of y = Deviations of y = see the attached excel file for the answer of each observation

Multiplications of the deviations of x and y = (x - Mean of x) * (y - Mean of y) = see the attached excel file for the answer of each observation

Sum of the multiplications of deviations of x and y = Sum of ((x - Mean of x) * (y - Mean of y)) = –5

Since we are using a sample, we use (N – 1) in our covariance between x and y as follows:

Covariance between x and y = Sum of ((x - Mean of x) * (y - Mean of y)) / (N – 1) = –5 / (5 – 1) = –5 / 4 = –1.25

b. Calculate the correlation coefficient (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal place.)

The correlation coefficient can be calculated using the following formula:

Correlation coefficient = Covariance between x and y / (Sum of (x - Mean of x)^2 * Sum of  (y - Mean of y)^2)^0.5 ………………… (1)

Where, from the attached excel file;

Covariance between x and y = –5

Sum of (x - Mean of x)^2 = 118

Sum of (y - Mean of y)^2 = 46

Substituting the values into equation (1), we have:

Correlation coefficient = –5 / (118 * 46)^0.5 = –5 / 5,428^0.5 = –5 / 73.6750 = – 0.07

Final answer:

The covariance between two variables can be calculated by first finding the mean of each dataset, subtracting the mean from each data point, multiplying the results for each pair of coordinates, summing these products to obtain the numerator. The denominator is obtained by subtracting one from the number of data points. The covariance is then the numerator divided by the denominator.

Explanation:

The term covariance is one of the key factors for understanding correlation between two variables. To calculate the covariance between the two given variables, we first need to calculate the mean of each set (x and y). After we've gotten the mean, we subtract the mean from each data point and multiply the results for each pair of x and y values. Summing these products will give us the numerator in the covariance calculation. The denominator is calculated by subtracting one from the total number of data points we have (n-1). So, the covariance is the sum we got from the numerator, divided by the denominator. Please don't forget to indicate if the covariance is negative, using a minus sign.

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You can use the fact that the 90% confidence interval given is all positive value for the test statistic being the difference of and .

The conclusion that is supported by the given confidence interval is given by:

Option C: There is evidence to conclude that because all values in the interval are positive.

How can we conclude that there is evidence that  ?

Since it is given that the difference is measured by ,

and  since the given confidence interval at 90% confidence for that difference is obtained to be (0.247,0.325), thus we can say that 90% difference value of   , will be lying in that given interval.

Since the interval is all positive, thus we can say that 90% of the times, the difference   will be positive which indicates that

Thus, the conclusion that is supported by the interval is given by:

Option C: There is evidence to conclude that because all values in the interval are positive.

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Answer:

C

Step-by-step explanation:

Statistics!!

When we have a confidence interval for the difference in proportions or means, our null hypothesis is always that there's no difference. (H0 = p1-p2 = 0.)

If the difference is positive, that means we have sufficient evidence p1>p2.

If it's negative, then we have sufficient evidence p2>p1.

Why not A: incorrect interpretation of the interval

Why not B: doesn't look like a complete answer

Why not D: also doesn't look like a complete answer

Why not E: this confuses the definition of alpha-level and p-value with confidence interval values. If those were p-values and greater or less than an alpha-level, we would reject or fail to reject the null hypothesis. That isn't the case here.

Answer: I got -1024...

Step-by-step explanation:

Final answer:

Due to insufficient information, we cannot calculate the determinant of the given matrix. The determinant calculation varies based on the matrix's size and the specifics of its elements.

Explanation:

The question asked was to find the determinant of a given matrix when the det(a) = 2. However, the information provided is insufficient to determine the actual matrix determinant due to numerical errors and unrelatable data. The determinant of a matrix is calculated differently depending on the type of matrix. For a 2x2 matrix, if the matrix is [a b; c d], the determinant would be 'ad - bc'. For a 3x3 matrix, the determinant process involves more steps including finding minors and cofactors of matrix elements. However, without the actual specifics of the matrix, the determinant cannot be calculated.

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There is a 0.95 probability that the sample mean will provide a margin of error of 7.84.

What is mean by Probability?

The term probability refers to the likelihood of an event occurring.

Given that;

The variance of a population = 1,936

And, A random sample of 121 has been taken from the population.

Now,

Since, Standard deviation = √ Variance

                                        = √1,936

                                        = 44

Hence, The standard error = 44 / √121

                                         = 44 /11

                                         = 4

We know that;

The critical z factor for a confident interval of 0.95 = ± 1.96

Thus, The sample mean will provide a margin of error = 4 × 1.96

                                                                                    = 7.84

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Answer:

It is known that the variance of a popualtion equals 1,936.

Step-by-step explanation:

That should be correct!!!