Answer:
59/100
Step-by-step explanation:
2*25+5+4=59
Answer:
Null hypothesis: The American Society for Certified Public Accountants says the average starting salary of accountants who graduated in 2018 is $57,413
Alternate hypothesis: The American Society for Certified Public Accountants says the average starting salary of accountants who graduated in 2018 is less than or equal to $57,413
Step-by-step explanation:
A null hypothesis is a statement from a population parameter that is subject to testing. It is expressed with equality.
An alternate hypothesis is also a statement from the population parameter that negates the null hypothesis. It is expressed with inequality
The required sum of -3x, 5x + y, and 7x - 8 - 3y in descending order is 9x - 2y - 8.
Simplification involves applying rules of arithmetic and algebra to remove unnecessary terms, factors, or operations from an expression. The goal is to obtain an expression that is easier to work with, manipulate, or solve.
Here,
To add -3x, 5x + y, and 7x - 8 - 3y, we can first combine like terms.
Group the x-terms together:
-3x + 5x + 7x = 9x
Group the y-terms together:
y - 3y = -2y
Group the constants together:
-8
Putting it all together, we get:
9x - 2y - 8
Therefore, the sum of -3x, 5x + y, and 7x - 8 - 3y in descending order is 9x - 2y - 8.
Learn more about simplification here:
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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
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.
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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