PATS, PETE AND KOFFI ANNUAL SALARIES AGGREGATE TO 200,000.00 A YEAR PETE MAKES $11000.00 MORE THAN KOFFI AND PAT MAKES $1000.00
1 answer:
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Mean = 12000
Standard Deviation = 2000
Our task is to determine how many standard deviations 14,500 is from the mean.
This requires us to compute the z-score
A z-score indicates how far a sample value is from the mean in terms of standard deviations. A positive z-score signifies that the sample value exceeds the mean.
The formula for calculating the z-score is = (Sample Value - Mean) / Standard Deviation
Thus,
Z-score =
This indicates that 14,500 is 1.25 standard deviations higher than the mean of 12,000.
Standard Deviation = 2000
Our task is to determine how many standard deviations 14,500 is from the mean.
This requires us to compute the z-score
A z-score indicates how far a sample value is from the mean in terms of standard deviations. A positive z-score signifies that the sample value exceeds the mean.
The formula for calculating the z-score is = (Sample Value - Mean) / Standard Deviation
Thus,
Z-score =
This indicates that 14,500 is 1.25 standard deviations higher than the mean of 12,000.
Answer:
- The profit can be expressed as 70x + 50
- If 240 phones are sold, the profit amounts to $16,850
Detailed explanation:
The revenue function R(x) is provided as
The cost function C(x) is given as
Profit is calculated by subtracting cost from revenue, expressed as Profit = Revenue − Cost
We substitute the given revenue and cost functions into this formula.
Denote the profit function as P(x).
Therefore, the profit function formula simplifies to 70x + 50
Since x denotes the quantity of phones sold, to find the profit when 240 phones are sold, we substitute x = 240 into the profit expression above.
Hence, selling 240 phones yields a profit of $16,850
Answer:
Step-by-step explanation:
Notation
is the sample mean
indicates the population mean (the variable of interest)
s signifies the sample standard deviation
n denotes the sample size
Solution to the problem
The mean's confidence interval is derived from the following formula:
(1)
In this instance, the 9% confidence interval corresponds to:
We can determine the mean using the following:
Additionally, the margin of error can be calculated as:
The margin of error for this situation is expressed as:
Next, we find the standard error:
The critical value for a 95% confidence interval using a normal standard distribution is roughly 1.96, and substituting gives us:
For the 98% confidence interval, the significance corresponds to and
with a critical value of 2.326, yielding a confidence interval of: