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A small standard deviation indicates that the data points in a dataset are close to the mean or average value. This suggests that the data is less spread out and more consistent, with less variability among the values. A small standard deviation may indicate that the data points are clustered around the mean.
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Which measure would you use to fine the spread of marks in an examination?
The measure commonly used to find the spread of marks in an examination is the standard deviation. It provides a numerical value that indicates how spread out the scores are from the mean score. A larger standard deviation suggests a wider spread of scores, while a smaller standard deviation indicates a more clustered distribution of scores.
How are Stanford-Binet intelligence scale results measured?
Stanford-Binet intelligence scale results are measured by calculating the individual's intelligence quotient (IQ). This is done by comparing the person's performance on the test to the performance of others in the same age group. The IQ score is a standardized measure that represents a person's cognitive abilities compared to the general population.
What does Relative standard deviation tells us?
Relative Standard Deviation (RSD) is a measure of precision (not accuracy). RSD is sometimes called coefficient of variation (CV) and often is calculated as a percentage. s = standard deviation x = mean RSD = s/x, as a percentage, (s/x) *100 The RSD allows standard deviations of different measurements to be compared more meaningfully. For example, if one is measuring the concentration of two compounds A and B and the result is 0.5 (+/-) 0.4 ng/mL for compound A and 10 (+/-) 2 ng/mL for compound B, one may look at the standard deviation for compound A and say because it is lower (0.4 vs. 2) than for B, the measurement for A was more precise. Actually this is not the case. When the %RSD is used the new values for compound A and B are 0.5 (+/-) 80% and 10 (+/-) 20% respectively, therefore, the measurement for compound B is more precise.
Z-score calculation formula with examples?
The formula to calculate the z-score of a data point is: ( z = \frac{(x - \mu)}{\sigma} ), where (x) is the data point, (\mu) is the mean of the data set, and (\sigma) is the standard deviation. For example, if you have a data point of 85, a mean of 75, and a standard deviation of 5, the z-score would be ( z = \frac{(85 - 75)}{5} = 2 ). This means the data point is 2 standard deviations above the mean.
What do standard deviation error bars indicate when they go past your minimum value?
If the minimum value is the minimum observed value then it indicates that the distribution goes below the minimum observed value.If the minimum value is the minimum defined for the distribution then it indicates thatthe data do not come from the proposed distribution,estimates for the mean or standard deviation are incorrect, oryou have got a sample which is atypical.
If the standard deviation is small the data is more dispersed?
No, if the standard deviation is small the data is less dispersed.
What does large standard deviation signify?
That there is quite a large amount of variation between the observations.
Is the standard deviation best thought of as the distance from the mean?
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
What does standard deviation show us about a set of scores?
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
Where the standard deviation is not applicable?
When the sample size is small
What are the assumptions of standard deviation?
The standard deviation is the standard deviation! Its calculation requires no assumption.
What a large standard deviation means?
A large standard deviation means that the data were spread out. It is relative whether or not you consider a standard deviation to be "large" or not, but a larger standard deviation always means that the data is more spread out than a smaller one. For example, if the mean was 60, and the standard deviation was 1, then this is a small standard deviation. The data is not spread out and a score of 74 or 43 would be highly unlikely, almost impossible. However, if the mean was 60 and the standard deviation was 20, then this would be a large standard deviation. The data is spread out more and a score of 74 or 43 wouldn't be odd or unusual at all.
What does the sample standard deviation best estimate?
The standard deviation of the population. the standard deviation of the population.
What is standard deviation of 155.45?
The standard deviation is 0.
What combination of factors will produce the smallest value for the standard error?
A small sample and a large standard deviation
If quartile deviation is 24. find mean deviation and standard deviation?
Information is not sufficient to find mean deviation and standard deviation.
What is the relationship between standard deviation and variance?
Standard deviation is the square root of the variance.
