30% is equivalent to 3/10
So any fraction that can be simplified to 3/10.
Another way to to think about it if you multiply 3/10 by any number over it self because that is equivalent to 1.
Like 3/10 * 2/2 =6/20 is also equal to 30%
Answer:
28⁰ = 1
Step-by-step explanation:
If you raise a number to the power of zero, it becomes 1, regardless of the number. The only exception is 0⁰, which is undefined. Any other value to the power of zero equals one.
The easiest way to see it is like this:
Pick any value, we'll call it x
x⁴ = x⁵ / x
x³ = x⁴ / x
x² = x³ / x
x¹ = x² / x
x⁰ = x¹ / x
Because x¹ is equal to x, then x⁰ is just x/x, which is always equal to 1, unless x is equal to zero.
The correct formula for this is as follows:
where n is the number of compounding periods per year, and r is the annual interest rate as a decimal,
Plugging the given values into the formula, we get:
This equation can be simplified to:
Taking logs of both sides gives:
which can be rearranged to get:
So it will take about 5.864 years for the amount to reach $4550.
Answer:x>-3
Step-by-step explanation:
Answer:
- Mean will Increase .
- Median remains unchanged.
- Standard deviation will increase.
Step-by-step explanation:
We are given that there are 14 employees in a particular division of a company and their salaries have a mean of $70,000, a median of $55,000, and a standard deviation of $20,000.
And also the largest number on the list is $100,000 but By accident, this number is changed to $1,000,000.
Now we have to analyse the Effect of this change in data values on mean, median, and standard deviation.
- Mean will get affected because $1,000,000 is a very huge value as compared to $100,000 and is considered to be an outlier and we know that mean is affected by outliers as mean will change to $134285.7143 after replacing $100,000 with $1,000,000 .
- Median will not get affected as median the middle most value in the data set and since $1,000,000 is considered to be an outlier so median remain unchanged at $55,000 .
- Standard Deviation will also get affected as due to outlier value in the data set the numerator value will increase very much and due to which standard deviation will also increase.
