or 5 lengths of 234 feet to be cut from a board, the board must have a length of at least 1170 feet.
Let x represent the total length of the board so as to allow for the cutting of 5 lengths.
Since each length needed to be cut is 234 feet, hence:
x = number of lengths × feet per board
x = 5 lengths × 234 feet
x = 1170 feet
Hence for 5 lengths of 234 feet to be cut from a board, the board must have a length of at least 1170 feet.
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These listed below would best help an athlete be successful in strategy training. Attitude is main strategy which can determine how much you can achieve.
Time of training should be for approx. 45-60 minutes to improve fitness.
To overcome the failures and to achieve goals, it is essential to have a person compelling vision. A lot of athletes achieve success after failures due to their vision. They have a dream which motivates them to perform better.
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</h3><h3>
Which person is known as athlete?</h3>
A person who is expert in sports and other forms of physical exercise.
Athlete should set goals which is considered to be the first step in the process of achieving success. Goals keep successful athletes motivated in the ground while playing.
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Answer:
Adaptability, persistence and hard work, these are the keys to success in small business, but they are three important attributes no matter what your endeavor.
Explanation:
Using the Central Limit Theorem, it is found that the valid conclusion is given as follows:
The sampling distribution will probably not follow a normal distribution, hence we cannot draw a conclusion.
<h3>Central Limit Theorem</h3>
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean 
and standard deviation 
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation 
.
For a skewed variable, the sampling distribution is also approximately normal, as long as n is at least 30.
In this problem, we have a skewed variable with a sample size less than 30, hence the Central Limit Theorem cannot be applied and the correct conclusion is:
The sampling distribution will probably not follow a normal distribution, hence we cannot draw a conclusion.
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Answer:
Both are normal distributions but standard normal distribution is a particular case of Normal distribution when the mean is 0 and standard deviation or variance is 1. This makes Y a “Standard” distribution. So basically X is Normally distributed and Y is “Standard” normally distributed.
