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When data includes a few extremely large or extremely small value it might be best to use a median value from the sample?
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∙ 10y ago
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Wiki User
∙ 10y ago
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Why is a large sample better than a small sample?
A large sample will reduce the effects of random variations.
Disadvantages of a large sample size confidence Interval in statistices?
A disadvantage to a large sample size can skew the numbers. It is better to have sample sizes that are appropriate based on the data.
A sample average can be used to estimate a population average precision if the sample is?
large
What two features must a sample have if its to accurately represent a population?
The sample must be large and random.
At a large University a simple random sample of 5 female professors is selected and a simple random sample of 10 male professors is selected The two samples are combined to give an overall sample of?
at a large university a simple random sample of 5 female proffesors is seleted and a simple random sample of 10 male professors is selected. the two samples are combine to give an overall sample of 15 professor. the overall sample is?
What can the difference between mean and median values infer. If the mean is 8 655.7 and the median -8 653.0?
First, I will give an example, similar to your question: -11000 -9000 +44000 mean = 8,000 and median = -9000. Symmetrical distributions after infinite sampling will show no difference in mean and median. Large differences are possible with small sample sizes even with symmetrical distributions. If the sample is large and the difference is large, this infers that the distribution is asymmetrical. The skewness of the distribution can be calculated.
Which level of measurement is required for the median?
It can be computer for ordinal level data or higher. It is NOT effected by extremely large or small numbers
A single, extremely large value can affect the median more than the mean?
A single, extremely large value can affect the median more than the mean because One-half of all the data values will fall above the mode, and one-half will fall below the mode. In a data set, the mode will always be unique. The range and midrange are both measures of variation.
Why is a large sample better than a small sample?
A large sample will reduce the effects of random variations.
If there is a small difference such as 5 600 and 5 602 between mean and median values what does this mean?
If the sample is small or not randomly chosen, it may not have much meaning at all. If the random sample is large, it would generally be inferred that the distribution is symmetrical. The skewness of the data can be calculated.
Owens orchards sells apples in a large bag by weikght a sample of seven bags contained the following numbers of apples 23192617212422 compute the mean number and median number of apples in a b?
Alot
Advantages and disadvantages of using arithmetic mean?
"The advantage is that the mean takes every value into account. A disadvantage is that it can be affected by extreme values. " The mean or more properly the "arithmetic mean" of a sample will eventually approximate the mean of the distribution of the population as the sample size increases. If the population distribution is skewed (not symmetrical), the mode and median will not provide an estimate of the mean, even as the sample size becomes large.
Disadvantages of a large sample size confidence Interval in statistices?
A disadvantage to a large sample size can skew the numbers. It is better to have sample sizes that are appropriate based on the data.
A sample average can be used to estimate a population average precision if the sample is?
large
What is used to create a large sample of DNA for testing for a small sample of DNA?
PCR
What two features must a sample have if its to accurately represent a population?
The sample must be large and random.
Why does a statistical sample have to be large?
The larger the sample of data collected leads to a more accurate conclusion.
