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What else can I help you with?
Is the uniform probability distribution's standard deviation proportional to the distribution's range?
no
When do you know when to use t-distribution opposed to the z-distribution?
z- statistics is applied under two conditions: 1. when the population standard deviation is known. 2. when the sample size is large. In the absence of the parameter sigma when we use its estimate s, the distribution of z remains no longer normal but changes to t distribution. this modification depends on the degrees of freedom available for the estimation of sigma or standard deviation. hope this will help u.... mona upreti.. :)
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.
Can The standard deviation of a distribution be a negative value?
No. The standard deviation is not exactly a value but rather how far a score deviates from the mean.
When the population standard deviation is unknown the sampling distribution is equal to what?
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
Your teacher presented the distribution of grades on the last quiz. What type of statistics did she use to convey this information descriptive statistics or Inferential statistics?
Descriptive statistics. Descriptive statistics are used to summarize and present data in an informative way, providing characteristics of the data set such as mean, median, mode, and standard deviation. Inferential statistics, on the other hand, are used to make inferences or predictions about a population based on sample data.
Symmetrical distribution in statistics and an example?
mean deviation is minimum
Why we calculate the variance and standard deviation?
They are measures of the spread of the data and constitute one of the key descriptive statistics.
What are examples of the relationship between descriptive and inferential statistics?
Descriptive statistics summarize and present data, while inferential statistics use sample data to make conclusions about a population. For example, mean and standard deviation are descriptive statistics that describe a dataset, while a t-test is an inferential statistic used to compare means of two groups and make inferences about the population.
What are the different divisions of statistics?
Parametric and non-parametric statistics.Another division is descriptive and inferential statistics.Descriptive and Inferential statistics. Descriptive statistics describes a population (e.g. mean, median, variance, standard deviation, percentages). Inferential infers some information about a population (e.g. hypothesis testing, confidence intervals, ANOVA).
What is relevant statistics?
Relevant statistics contain data that directly answers the question researchers analyzed. Findings include samples with standard deviation, distribution, and variance included.
In statistics what does SE stand for. Someone asked this question and I have the answer can you find the person who posted this question?
SE stands for ''standard error'' in statistics. Thanx Sylvia It is the same as the standard deviation of a sampling distribution, such as the sampling distribution of the mean.
What are the two parameters that are necessary to determine probabilities for a particular normal distribution curve?
Mean and Standard Deviation
What is the standard deviation of a standard normal distribution?
The standard deviation in a standard normal distribution is 1.
Does descriptive statistics means parametric statistics?
No. Descriptive statistics are those that characterise samples without attempting to draw conclusions. The purpose of them is to help investigators to form an understanding of what the data might be capable of telling them. Descriptive statistics include graphs as well as measures of location, scale, correlation, and so on. Parametric statistics are those that are based on probabilistic models (ie, mathematical models involving probability) that involve parameters. For instance, an investigator might assume that her results have come from a population that is normally distributed with a certain mean and standard deviation; this would be a parametric model. She could estimate this pair of parameters, the mean and standard deviation, using parametric statistics, or test hypotheses about them, again using parametric statistics. In either case the parametric statistics she uses would be based on the parametric mathematical model she has chosen for her data.
In the standard normal distribution the standard deviation is always what?
The standard deviation in a standard normal distribution is 1.
How do you use the z-score to determine a normal curve?
If the Z-Score corresponds to the standard deviation, then the distribution is "normal", or Gaussian.
