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What type of distribution pattern that occurs when the majority of the data values fall to the left of the mean?
Slhamma
positively skewed
Wiki User
∙ 12y ago
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What type of distribution of a set of data that shows nearly the same frequency for all values?
The Uniform Distribution.
If a great many data values cluster to the left of a data distribution which then tails off to the right the distribution is referred to as?
It is a positively skewed distribution.
Does cumulative frequency show distribution?
Not directly, but the cumulative frequency contains the same information as the frequencies for the values in question. However, it may not show the full details of the distribution if the values have been grouped.
What is the difference between a discrete and a continuous distribution?
A simple continuous distribution can take any value between two other values whereas a discrete distribution cannot.
A grouped frequency distribution is used when the range of data values is relatively small. True or false?
False. When the range is large you would use a grouped frequency distribution.
What does data distribution mean?
It is the set of values that a variable can take together with the probability or frequency distribution for those values.
What is distribution in math?
Distribution is the set of values that a variable can take, along with measures relating to the likelihood of the variable taking those values.
What distribution that has a great number of values on one side?
The answer depends on one side of WHAT! There is no distribution which has a greater number of values on either side of its median.
What are modes of distribution?
The data values with the highest frequency, gives the peak of the distribution graph.
What type of distribution of a set of data that shows nearly the same frequency for all values?
The Uniform Distribution.
If a great many data values cluster to the left of a data distribution which then tails off to the right the distribution is referred to as?
It is a positively skewed distribution.
One of the values of a variable which divides the distribution of the variable?
A quantile.
Why is the standard deviation of a distribution of means smaller than the standard deviation of the population from which it was derived?
The reason the standard deviation of a distribution of means is smaller than the standard deviation of the population from which it was derived is actually quite logical. Keep in mind that standard deviation is the square root of variance. Variance is quite simply an expression of the variation among values in the population. Each of the means within the distribution of means is comprised of a sample of values taken randomly from the population. While it is possible for a random sample of multiple values to have come from one extreme or the other of the population distribution, it is unlikely. Generally, each sample will consist of some values on the lower end of the distribution, some from the higher end, and most from near the middle. In most cases, the values (both extremes and middle values) within each sample will balance out and average out to somewhere toward the middle of the population distribution. So the mean of each sample is likely to be close to the mean of the population and unlikely to be extreme in either direction. Because the majority of the means in a distribution of means will fall closer to the population mean than many of the individual values in the population, there is less variation among the distribution of means than among individual values in the population from which it was derived. Because there is less variation, the variance is lower, and thus, the square root of the variance - the standard deviation of the distribution of means - is less than the standard deviation of the population from which it was derived.
If the mean of a symmetric distribution is 130 which of these values could be the median of the distribution?
If it is a symmetric distribution, the median must be 130.
Does cumulative frequency show distribution?
Not directly, but the cumulative frequency contains the same information as the frequencies for the values in question. However, it may not show the full details of the distribution if the values have been grouped.
When your sample data is all negative values how can you convert it for use on a normal distribution?
The data from a normal distribution are symmetric about its mean, not about zero. There is, therefore nothing strange about all the values being negative.
Is the mean and median similar?
The Mean is the average of a given set of values. The Median is the value that has the same number of smaller values than the number of higher values, it is in the middle of them. In a symmetrical distribution the Mean is equal to the Median. In an asymmetrical distribution they have different value.
