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Probability
The probability of a certain event is a number expressing the likelihood that a specific event will occur, expressed as the ratio of the number of actual occurrences to the number of possible occurrences. In mathematics, it is a measure of how often an event will happen and is the basis of statistics.
14,643 Questions
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.
What is the probability of rolling a two and then a three?
If you roll a die often enough, it is a certainty.
If you roll a fair die just twice, the probability is 1/36.
We say that these are independent events, meaning that the outcome of rolling the cube does not influence what outcome of rotating the spinner. For each outcome of rolling the cube there are 10 outcomes from the spinner. We can therefore, multiply the numbers of possibilities: 6 * 10 = 60
One way of seeing this is to list the possible outcomes :
C1 S1
C1 S2
C1 S3
.
.
.
C1 S10
Notice that there are 10 spinner possibilities for one cube event. There are 5 more possible cube events, hence, 50 combination events.
The probability is 1 (a certainty) if 39 cards are drawn without replacement.
On a single random draw the probability is 14/52 = 7/26.
The probability is 1 (a certainty) if 39 cards are drawn without replacement.
On a single random draw the probability is 14/52 = 7/26.
The probability is 1 (a certainty) if 39 cards are drawn without replacement.
On a single random draw the probability is 14/52 = 7/26.
The probability is 1 (a certainty) if 39 cards are drawn without replacement.
On a single random draw the probability is 14/52 = 7/26.
What is the probability of drawing a card less than 6 from a deck of cards?
Counting Ace as less than 6, then there are 20 cards out of 52 less than 6, for a probability 5/13.
Counting Ace as high with 2 being the lowest card, there are 16 cards less than 6 for a probability of 4/13.
What is the probability of flipping 4 coins and getting 3 tails?
If they are fair coins, the probability is 0.25
Where can one see the odds of a bet?
There are a few options that are available to see betting odds. This would greatly depend on what odds one is interested in viewing, but one can find betting odds on sites such as Odds Checker, Odds Portal and Odds Shark.
Which distribution describes the probability of r occurrences in n trials of an event?
The answer depends on whether or not the events are independent, whether or not the probabilities are the same for each event etc. Without that information, there cannot be an answer.
Why there is probability of getting hurt when you fall from certain height?
If you fall from any given height, whether or not you get hurt will depend on a large number of factors: what you fall on, how you fall, whether or not there was something that broke your fall on the way down and so forth.
What is the relationship between confidence interval and standard deviation?
Short answer, complex. I presume you're in a basic stats class so your dealing with something like a normal distribution however (or something else very standard). You can think of it this way...
A confidence interval re-scales margin of likely error into a range. This allows you to say something along the lines, "I can say with 95% confidence that the mean/variance/whatever lies within whatever and whatever" because you're taking into account the likely error in your prediction (as long as the distribution is what you think it is and all stats are what you think they are).
This is because, if you know all of the things I listed with absolute certainty, you are able to accurately predict how erroneous your prediction will be. It's because central limit theory allow you to assume statistically relevance of the sample, even given an infinite population of data.
The main idea of a confidence interval is to create and interval which is likely to include a population parameter within that interval. Sample data is the source of the confidence interval. You will use your best point estimate which may be the sample mean or the sample proportion, depending on what the problems asks for. Then, you add or subtract the margin of error to get the actual interval. To compute the margin of error, you will always use or calculate a standard deviation.
An example is the confidence interval for the mean. The best point estimate for the population mean is the sample mean according to the central limit theorem.
So you add and subtract the margin of error from that. Now the margin of error in the case of confidence intervals for the mean is za/2 x Sigma/ Square root of n where a is 1- confidence level. For example, confidence level is 95%, a=1-.95=.05 and a/2 is .025. So we use the z score the corresponds to .025 in each tail of the standard normal distribution. This will be. z=1.96. So if Sigma is the population standard deviation, than Sigma/square root of n is called the standard error of the mean. It is the standard deviation of the sampling distribution of all the means for every possible sample of size n take from your population ( Central limit theorem again). So our confidence interval is the sample mean + or - 1.96 ( Population Standard deviation/ square root of sample size.
If we don't know the population standard deviation, we use the sample one but then we must use a t distribution instead of a z one. So we replace the z score with an appropriate t score.
In the case of confidence interval for a proportion, we compute and use the standard deviation of the distribution of all the proportions. Once again, the central limit theorem tells us to do this. I will post a link for that theorem.
It is the key to really understanding what is going on here!
What is the probability Of obtaining tails and five?
The answer to what I think the question might be, is (1/2)*(1/6) = 1/12
What percentage of normally distributed scores lie under the normal curve?
100%. And that is true for any probability distribution.
How the total area under the normal curve is equal to one?
Please see the link under "legitimate probability density function".
Where can one buy a rolling file cabinet?
Some of the places that one can buy a rolling file cabinet are Office Depot and Quill. Some of the other retailers where one could purchase a rolling file cabinet are Staples, Ikea, Target and Walmart.
What is the primary characteristic of a probability sample?
In the context of a sample of size n out of a population of N, any sample of size n has the same probability of being selected. This is equivalent to the statement that any member of the population has the same probability of being included in the sample.
How do you derive mean deviation from mean for pareto distribution?
The total deviation from the mean for ANY distribution is always zero.
How do you calculate relative frequency probability?
You carry out an experiment repeatedly. Then the number of times that the selected even occurs divided by the total number of trials is the relative probability for that event.
Where can one purchase a Jansport rolling backpack?
One can purchase a Jansport rolling backpack directly from jansport, Sears, and Amazon. Other retailers of the Jansport rolling backpack include eBay and Dicks Sporting Good.
What is the probability of flipping 3 coins and getting all heads or tails?
The probabilty of you flipping 3 coins and getting all heads or tails is 0.125 or 1/8.
What is the probability that at least 2 people have the same birth month in a group of 8 people?
Birth months are not uniformly distributed across the year. However, if yo assume that they are, the probability is 0.9536 (approx).
What is the probability of a birthday falling on Monday?
The standard answer for school work is 1/7. However, the reality may be slightly different since in parts of the world, particularly where induced hospital births are relatively common, it is claimed that births are brought forward so that medical staff can spend their weekend with their own families.
What is the probability of drawing a 6 of hearts?
The answer depends on how many cards are drawn, whether or not at random, from an ordinary deck of cards, with or without replacement. The probability for a single card, drawn at random, from a normal deck of playing cards is 1/52.
