A normal data set is a set of observations from a Gaussian distribution, which is also called the Normal distribution.
standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.
The answer will depend on the data values: there is no rule that fits all situations.
There are a number of appropriate displays to show the measures of variation for a data set. Different graphs can be used for this purpose which may include histograms, stemplots, dotplots and boxplots among others.
No.The empirical rule is a good estimate of the spread of the data given the mean and standard deviation of a data set that follows the normal distribution.If you you have a data set with 10 values, perhaps all 10 the same, you clearly cannot use the empirical rule.
A normal data set is a set of observations from a Gaussian distribution, which is also called the Normal distribution.
Different types of graphs are appropriate for different types of data.
when does it make sense to choose a linear function to model a set of data
standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.
hello i discovered answer: Assessing the scope of a model, that is, determining what situations the model is applicable to, can be less straightforward. If the model was constructed based on a set of data, one must determine for which systems or situations the known data is a "typical" set of data.
The normal distribution allows you to measure the distribution of a set of data points. It helps to determine the average (mean) of the data and how spread out the data is (standard deviation). By using the normal distribution, you can make predictions about the likelihood of certain values occurring within the data set.
None. The data set has no elements and so there cannot be any central tendency.
The answer will depend on the data values: there is no rule that fits all situations.
The most appropriate measures of center for a data set depend on its distribution. If the data is normally distributed, the mean is a suitable measure of center; however, if the data is skewed or contains outliers, the median is more appropriate. For measures of spread, the standard deviation is ideal for normally distributed data, while the interquartile range (IQR) is better for skewed data or when outliers are present, as it focuses on the middle 50% of the data.
There are a number of appropriate displays to show the measures of variation for a data set. Different graphs can be used for this purpose which may include histograms, stemplots, dotplots and boxplots among others.
In computer science, data modeling is the process of creating a data model by applying a data model theory to create a data model instance. A data model theory is a formal data model description.For the source and more detailed information concerning your request, click on the related links section (Answers.com) indicated below.
The computation form for sample variance is?