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The mean and standard deviation are usually not used together because of outliers?

false


If outliers are added to a dataset how would the variance and standard deviation change?

They would both increase.


What is the relation between quartile deviation and standard deviation?

Strictly speaking, none. A quartile deviation is a quick and easy method to get a measure of the spread which takes account of only some of the data. The standard deviation is a detailed measure which uses all the data. Also, because the standard deviation uses all the observations it can be unduly influenced by any outliers in the data. On the other hand, because the quartile deviation ignores the smallest 25% and the largest 25% of of the observations, there are no outliers.


Is mean deviation less than standard deviation?

Yes, the mean deviation is typically less than or equal to the standard deviation for a given dataset. The mean deviation measures the average absolute deviations from the mean, while the standard deviation takes into account the squared deviations, which can amplify the effect of outliers. Consequently, the standard deviation is usually greater than or equal to the mean deviation, but they can be equal in certain cases, such as when all data points are identical.


Does the outlier affect the standard deviation?

Yes, outliers can significantly affect the standard deviation. Since standard deviation measures the dispersion of data points from the mean, the presence of an outlier can increase the overall variability, leading to a higher standard deviation. This can distort the true representation of the data's spread and may not accurately reflect the typical data points in the dataset.


Which of the following is least affected if an extreme high outlier is added to your data mean median or standard deviation or ALL?

The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.


Is absolute mean deviation affected by outliers?

Yes.


What is a good standard deviation for a stock?

A good standard deviation for a stock is typically around 15-20. This indicates moderate volatility in the stock's price movements.


What determines numerical measures of center and spread are appropriate for describing a given distribution of quantitative variable?

The choice of numerical measures of center (mean, median) and spread (range, variance, standard deviation, interquartile range) depends on the distribution's shape and characteristics. For symmetric distributions without outliers, the mean and standard deviation are appropriate, while for skewed distributions or those with outliers, the median and interquartile range are more robust choices. Additionally, the presence of outliers can significantly affect the mean and standard deviation, making alternative measures more reliable. Understanding the data's distribution helps ensure that the selected measures accurately represent its central tendency and variability.


What are the assumptions of standard deviation?

The standard deviation is the standard deviation! Its calculation requires no assumption.


Who is statement below is correct concerning outliers?

To accurately assess the correctness of statements concerning outliers, I would need to see the specific statements in question. In general, outliers are data points that differ significantly from the overall pattern of data, and they can influence statistical analyses, such as mean and standard deviation. Identifying outliers is important for understanding data distribution and ensuring the robustness of statistical conclusions.


What does the sample standard deviation best estimate?

The standard deviation of the population. the standard deviation of the population.