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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 does the term descriptive statistic include?
Descriptive statistics encompass methods for summarizing and organizing data to provide a clear overview of its main characteristics. This includes measures of central tendency, such as mean, median, and mode, which represent the average or typical values. Additionally, it involves measures of variability, such as range, variance, and standard deviation, which describe the spread or dispersion of the data. Descriptive statistics also include visual representations like charts and graphs to facilitate understanding of the data's distribution.
Which descriptive statistics are appropriate for qualitative variables and what are appropriate for quantitative variables and why?
For qualitative variables, appropriate descriptive statistics include frequencies and proportions, as they help summarize categorical data and show the distribution of different categories. For quantitative variables, measures such as mean, median, mode, range, variance, and standard deviation are suitable because they provide insights into the central tendency, spread, and overall distribution of numerical data. The choice of statistics depends on the nature of the data: qualitative data is categorical and non-numeric, while quantitative data is numeric and can be measured.
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.
How do you determine your sample score on the comparison distribution?
To determine your sample score on the comparison distribution, you first need to calculate the sample mean and standard deviation. Then, you can use these statistics to find the z-score, which indicates how many standard deviations your sample mean is from the population mean. By comparing this z-score to critical values from the standard normal distribution, you can assess the significance of your sample score in relation to the comparison distribution.
What are the two parameters that are necessary to determine probabilities for a particular normal distribution curve?
Mean and Standard Deviation
What is a t distribution?
The t distribution is a probability distribution that is symmetric and bell-shaped, similar to the normal distribution, but has heavier tails. It is used in statistics, particularly for small sample sizes, to estimate population parameters when the population standard deviation is unknown. The t distribution accounts for the additional uncertainty introduced by estimating the standard deviation from the sample. As the sample size increases, the t distribution approaches the normal distribution.
