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An estimate is an educated guess. Approximate and round off mean "about".
In some cases a choice of tests may be available; some tests are more powerful than others.Use a larger sample.There is a trade-off between Type I and Type II errors so you can always reduce the Type I error by allowing the Type II error to increase.
The optimum sample size is based on a trade-off between the precision required for the estimate(s) and the cost of sampling. The precision required depends on the consequences of making the wrong decision. I would expect much higher precision for a medical trial than I would for a weather forecast.The necessary sample size, to attain that precision will depend on the characteristic that is being estimated (mean, variance, proportion), the underlying distribution and the test being used. Then there is the cost (money and time) that depend on the sample size.Since you have not bothered to share any information on any of these factors, I cannot provide a more useful answer.The optimum sample size is based on a trade-off between the precision required for the estimate(s) and the cost of sampling. The precision required depends on the consequences of making the wrong decision. I would expect much higher precision for a medical trial than I would for a weather forecast.The necessary sample size, to attain that precision will depend on the characteristic that is being estimated (mean, variance, proportion), the underlying distribution and the test being used. Then there is the cost (money and time) that depend on the sample size.Since you have not bothered to share any information on any of these factors, I cannot provide a more useful answer.The optimum sample size is based on a trade-off between the precision required for the estimate(s) and the cost of sampling. The precision required depends on the consequences of making the wrong decision. I would expect much higher precision for a medical trial than I would for a weather forecast.The necessary sample size, to attain that precision will depend on the characteristic that is being estimated (mean, variance, proportion), the underlying distribution and the test being used. Then there is the cost (money and time) that depend on the sample size.Since you have not bothered to share any information on any of these factors, I cannot provide a more useful answer.The optimum sample size is based on a trade-off between the precision required for the estimate(s) and the cost of sampling. The precision required depends on the consequences of making the wrong decision. I would expect much higher precision for a medical trial than I would for a weather forecast.The necessary sample size, to attain that precision will depend on the characteristic that is being estimated (mean, variance, proportion), the underlying distribution and the test being used. Then there is the cost (money and time) that depend on the sample size.Since you have not bothered to share any information on any of these factors, I cannot provide a more useful answer.
The idea when using quartiles is take all your data and write it out in increasing order then divide it in 4 equal parts.The upperquartile is the part containing the highest data values, the uppermiddle quartile is the part containing the next-highest data values,the lower quartile is the part containing the lowest data values,while the lower middle quartile is the part containing the next-lowest data values.Here is the catch-------------- the terms can also refer to cut-off values between the 4 sets.The term 'upper quartilevcan becut-off value between the upper quartile subset and the upper middlequartile subset. And, the 'lower quartile' can refer to a cut-off value between the lower quartile setand the lower middle quartile set. usually we look at the interquartile range (IQR) which is the range between the thrird and 1st quartileIQR is used to make box plots and other cool graphs.The upper quartile (Q3) is the median of the upper half of the data set. Q3 cuts off highest 25% of data And just FYI: first quartile (designated Q1) = lower quartile = cuts off lowest 25% of data = 25th percentile second quartile (designated Q2) = median = cuts data set in half = 50th percentile
I think you left off some important information. Perhaps you can supply this information, to obtain assistance. To calculate the probability or the chance of occurrence between two values, we calculate: Pr{a < X < b} = F(b) - F(a) where F(x) = cumulative probability distribution. The distribution requires certain known parameters. In the case of the Normal distribution, the mean and standard deviation are parameters. In your particular case, a = 20 and b = 28.
Information such as the the value of the intellect of employee's may be considered relevant, but the reliability of this information is very low as it is difficult to determine a measurement for intellect.
trade off between ris and profitability
For most products you can buy, there is a trade-off between quality and price.
For most products you can buy, there is a trade-off between quality and price.
relevance is a technical word for on topic of irrelevant means off topic
to decide if its goood
Exchange.
a balance achieved between two desirable but incompatible features; a compromise
The basic trade- off in the investment process is between the anticipated rate of return for a given investment instrument and its degree of risk.
No.
The relationship between trade offs and opportunity costs is that they both have to do with Economics. A person has to make a choice that would have to sacrifice.
The relationship between trade offs and opportunity costs is that they both have to do with Economics. A person has to make a choice that would have to sacrifice.