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What price do farmers get for the peach crops In the third week of June a random sample mean of 6.88 per basket. Assume that the standard deviation is known to be 1.92 per basket. Find a 90 confidence?
Wiki User
∙ 6y ago
If there are any grounds for assuming that the prices are Normally distributed (in fact, there are none), then a 90% confidence interval is (3.72, 10.04).
Wiki User
∙ 6y ago
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Can standard deviation assume a negative value?
No. It is defined to be the positive square root of ((the sum squared deviation divided by (the number of observations less one))
How standard deviation formula can be used in in cement industry?
Usually, industrial use of standard deviation is involved in quality control and testing. A product such as cement, is produced in batches, and I assume, requires periodic testing to ensure consistent properties. The sample test variations can be evaluated using standard deviation. If the standard deviation is high, it is likely that inferior product could be shipped. Probability analysis can determine the chance that product below certain standards would be shipped.
Assume that aset of test scores is normally distributed with a mean of 100 and a standard deviation of 20 use the 68-95-99?
68% of the scores are within 1 standard deviation of the mean -80, 120 95% of the scores are within 2 standard deviations of the mean -60, 140 99.7% of the scores are within 3 standard deviations of the mean -40, 180
How do you find the interquartile range when given the mean and standard deviation?
In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.
Does a large percent Relative Standard Deviation number indicate less precision?
Only if you assume that the true values are supposed to be the same every time. Otherwise, it is also possible that there is, indeed, a lot of variation among the values.
Does variance and standard deviation assume nominal data?
No. Variance and standard deviation are dependent on, but calculated irrespective of the data. You do, of course, have to have some variation, otherwise, the variance and standard deviation will be zero.
How does one interpret a standard deviation which is more than the mean?
Standard deviation is a measure of the dispersion of the data. When the standard deviation is greater than the mean, a coefficient of variation is greater than one. See: http://en.wikipedia.org/wiki/Coefficient_of_variation If you assume the data is normally distributed, then the lower limit of the interval of the mean +/- one standard deviation (68% confidence interval) will be a negative value. If it is not realistic to have negative values, then the assumption of a normal distribution may be in error and you should consider other distributions. Common distributions with no negative values are gamma, log normal and exponential.
Can standard deviation assume a negative value?
No. It is defined to be the positive square root of ((the sum squared deviation divided by (the number of observations less one))
What does it mean when the standard deviation is 1?
A standard deviation is a statistical measure of the variation there in a population or group. A standard deviation of 1 means that 68% of the members of the population are withing plus or minus the value of the standard deviation from the average. For example: assume the average height of men is 5 feet 9 inches, and the standard deviation is three inches. Then 68% of all men are between 5' 6" and 6' which is 5'9" plus or minus 3 inches. [Note: this is only to illustrate and is not intended to be a real/correct statistic of men's heights.]
How standard deviation formula can be used in in cement industry?
Usually, industrial use of standard deviation is involved in quality control and testing. A product such as cement, is produced in batches, and I assume, requires periodic testing to ensure consistent properties. The sample test variations can be evaluated using standard deviation. If the standard deviation is high, it is likely that inferior product could be shipped. Probability analysis can determine the chance that product below certain standards would be shipped.
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.
Assume that X has a normal distribution with mean equals 15.2 and standard deviation equals 0.9 What is the probability that X is greater than 16.1?
0.8413
Assume that aset of test scores is normally distributed with a mean of 100 and a standard deviation of 20 use the 68-95-99?
68% of the scores are within 1 standard deviation of the mean -80, 120 95% of the scores are within 2 standard deviations of the mean -60, 140 99.7% of the scores are within 3 standard deviations of the mean -40, 180
What is sigma in statistics?
Since this is regarding statistics I assume you mean lower case sigma (σ) which, in statistics, is the symbol used for standard deviation, and σ2 is known as the variance.
How do you find the interquartile range when given the mean and standard deviation?
In general you cannot. You will need to know more about the distribution of the variable - you cannot assume that the distribution is uniform or Normal.
What is the purpose of finding the standard deviation of a data set?
The purpose of obtaining the standard deviation is to measure the dispersion data has from the mean. Data sets can be widely dispersed, or narrowly dispersed. The standard deviation measures the degree of dispersion. Each standard deviation has a percentage probability that a single datum will fall within that distance from the mean. One standard deviation of a normal distribution contains 66.67% of all data in a particular data set. Therefore, any single datum in the data has a 66.67% chance of falling within one standard deviation from the mean. 95% of all data in the data set will fall within two standard deviations of the mean. So, how does this help us in the real world? Well, I will use the world of finance/investments to illustrate real world application. In finance, we use the standard deviation and variance to measure risk of a particular investment. Assume the mean is 15%. That would indicate that we expect to earn a 15% return on an investment. However, we never earn what we expect, so we use the standard deviation to measure the likelihood the expected return will fall away from that expected return (or mean). If the standard deviation is 2%, we have a 66.67% chance the return will actually be between 13% and 17%. We expect a 95% chance that the return on the investment will yield an 11% to 19% return. The larger the standard deviation, the greater the risk involved with a particular investment. That is a real world example of how we use the standard deviation to measure risk, and expected return on an investment.
How do you calculate a priori probability when you know standard deviation and mean scores?
If it is possible to assume normality, simply convert the desired score to a z-score, and look up the probability for that.
