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The mode and standard deviation of a distribution are 55 and 4.33 respectively?
Wiki User
∙ 14y ago
The statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.
Wiki User
∙ 14y ago
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What are the two parameters that completely characterize a standarized normal distribution and mean and standard deviation?
mode and skew
Why do we have to compute for the mean median mode and standard deviation?
To obtain a much better, simpler, and more practical understanding of the data distribution.
How do solve the frequency distribution?
The answer will depend on what you mean by "solve". Find the mean, median, mode, variance, standard error, standard deviation, quartiles, deciles, percentiles, cumulative distribution, goodness of fit to some distribution etc. The question needs to be a bit more specific than "solve".
Characteristics of mean median mode range variance standard deviation mean absolute deviation?
characteristics of mean
Why are means mode median or standard deviation used?
'Mean', 'mode', 'median' and 'standard deviation' are all quantities used in statistics. Each one is an attempt to use a single number to describe the essential nature and character of a bunch of numbers.
What are the median and mode of a normal distribution if the mean is 22 and the standard deviation is 4?
The mean, median, and mode of a normal distribution are equal; in this case, 22. The standard deviation has no bearing on this question.
What are the two parameters that completely characterize a standarized normal distribution and mean and standard deviation?
mode and skew
Why do we have to compute for the mean median mode and standard deviation?
To obtain a much better, simpler, and more practical understanding of the data distribution.
What are importance of mean and standard deviation in the use of normal distribution?
For data sets having a normal distribution, the following properties depend on the mean and the standard deviation. This is known as the Empirical rule. About 68% of all values fall within 1 standard deviation of the mean About 95% of all values fall within 2 standard deviation of the mean About 99.7% of all values fall within 3 standard deviation of the mean. So given any value and given the mean and standard deviation, one can say right away where that value is compared to 60, 95 and 99 percent of the other values. The mean of the any distribution is a measure of centrality, but in case of the normal distribution, it is equal to the mode and median of the distribtion. The standard deviation is a measure of data dispersion or variability. In the case of the normal distribution, the mean and the standard deviation are the two parameters of the distribution, therefore they completely define the distribution. See: http://en.wikipedia.org/wiki/Normal_distribution
How do solve the frequency distribution?
The answer will depend on what you mean by "solve". Find the mean, median, mode, variance, standard error, standard deviation, quartiles, deciles, percentiles, cumulative distribution, goodness of fit to some distribution etc. The question needs to be a bit more specific than "solve".
What is the mean mode median standard deviation and standard error of 10 24 35 44 10 and 35?
Mean: 26.33 Median: 29.5 Mode: 10, 35 Standard Deviation: 14.1515 Standard Error: 5.7773
Is normal distribution symmetrical?
Yes. By definition. A normal distribution has a bell-shaped density curve described by its mean and standard deviation. The density curve is symmetrical(i.e., an exact reflection of form on opposite sides of a dividing line), and centered about (divided by) its mean, with its spread (width) determined by its standard deviation. Additionally, the mean, median, and mode of the distribution are equal and located at the peak (i.e., height of the curve).
Characteristics of mean median mode range variance standard deviation mean absolute deviation?
characteristics of mean
The Pearson's coefficient of skewness is a measure of distribution's symmetry?
It is a descriptive statistical measure used to measure the shape of the curve drawn from the frequency distribution or to measure the direction of variation. It is a measure of how far positively skewed (below the mean) or negatively skewed (above the mean) the majority (that's where the mode comes in) of the data lies. Useful when conducting a study using histograms. (mean - mode) / standard deviation. or [3(Mean-Median)]/Standard deviation
If mean is 8 median is 6 and standard deviation is 2 what is skewness?
Karl Pearson simplified the topic of skewness and gave us some formulas to help. The first is the Pearson mode or first skewness coefficient. It is defined by the (mean-median)/standard deviation. So in this case the Pearson mode is: (8-6)/2 =1 There is also the Pearson Median. This is also called second skewness coefficient. It is defined as 3(mean-median)/standard deviation which in this case is 6/2 =3 hence the distribution is positive skewed
Why are means mode median or standard deviation used?
'Mean', 'mode', 'median' and 'standard deviation' are all quantities used in statistics. Each one is an attempt to use a single number to describe the essential nature and character of a bunch of numbers.
How do you calculate mean median and standard deviation?
The mean is the sum of each sample divided by the number of samples.The median is the middle sample in a ranked list of samples, or the mean of the middle two samples if the number of samples is even.The standard deviation is the square root of the sum of the squares of the difference between the mean and each of the samples, such sum then divided by either N or by N-1, before the square root is taken. N is used for population standard deviation, where the mean is known independently of the calculation of the standard deviation. N-1 is used for sample standard deviation, where the mean is calculated along with the standard deviation, and the "-1" compensates for the loss of a "degree of freedom" that such a procedure entails.Not asked, but answered for completeness sake, the mode is the most probable value, and does not necessarily represent the mean such as in an asymmetrically skewed distribution, such as a Poisson distribution.
