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What does the median tell you about the distribution of a set of data?
the midpoint of the data set
Why you prefer normal distribution over other distributions in statistics?
we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.
What does probalility distribution mean?
In parametric statistical analysis we always have some probability distributions such as Normal, Binomial, Poisson uniform etc.In statistics we always work with data. So Probability distribution means "from which distribution the data are?
What distribution is a sampling distribution referring to?
A sampling distribution refers to the distribution from which data relating to a population follows. Information about the sampling distribution plus other information about the population can be inferred by appropriate analysis of samples taken from a distribution.
How to find Median of probability distribution?
how do i find the median of a continuous probability distribution
What is the mean of the sampling distribution of the sample mean?
Frequently it's impossible or impractical to test the entire universe of data to determine probabilities. So we test a small sub-set of the universal database and we call that the sample. Then using that sub-set of data we calculate its distribution, which is called the sample distribution. Normally we find the sample distribution has a bell shape, which we actually call the "normal distribution." When the data reflect the normal distribution of a sample, we call it the Student's t distribution to distinguish it from the normal distribution of a universe of data. The Student's t distribution is useful because with it and the small number of data we test, we can infer the probability distribution of the entire universal data set with some degree of confidence.
What is the sampling distribution of sample means and why is it useful?
Frequently it's impossible or impractical to test the entire universe of data to determine probabilities. So we test a small sub-set of the universal database and we call that the sample. Then using that sub-set of data we calculate its distribution, which is called the sample distribution. Normally we find the sample distribution has a bell shape, which we actually call the "normal distribution." When the data reflect the normal distribution of a sample, we call it the Student's t distribution to distinguish it from the normal distribution of a universe of data. The Student's t distribution is useful because with it and the small number of data we test, we can infer the probability distribution of the entire universal data set with some degree of confidence.
How is a frequency distribution used?
it is used to find mean<median and mode of grouped data
Why it is important to find the shape of data distribution before computing descriptive statistics?
to help determine and give insight into the data colleced.
Can frequency distribution contain qualitative data?
frequency distribution contain qualitative data
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.
What is a normal data set?
A normal data set is a set of observations from a Gaussian distribution, which is also called the Normal distribution.
What percentage of the data in a normal distribution is represented by 1 SD of a sample?
Assuming that we have a Normal Distribution of Data, approx. 65% of the data will fall within One Sigma.
What Percent of data is below the mean in a normal distribution?
In the normal distribution, the mean and median coincide, and 50% of the data are below the mean.
How can you describe what is typical about the distribution of a set of data?
The answer will depend on the set of data!
What does the median tell you about the distribution of a set of data?
the midpoint of the data set
What are some benefits of representing data sets using graphs of frequency distribution?
Organizing the data into a frequency distribution may make patterns within the data more evident.
