hey u can choose any number from the frequency to find the assumed mean
suppose u have 8 frequencies u can assume 4 as the mean
Your question is a bit difficult to understand. I will rephrase: In hypothesis testing, when the sample mean is close to the assumed mean of the population (null hypotheses), what does that tell you? Answer: For a given sample size n and an alpha value, the closer the calculated mean is to the assumed mean of the population, the higher chance that null hypothesis will not be rejected in favor of the alternative hypothesis.
First of all, one needs to understand that this is another method of finding the Mean of a list of data. Sometimes the data is presented in a form which makes the calculation of the mean by the usual method impossible. Such a situation would involve a frequency table where the data is presented as an interval. For example, a question might be, "A person rolls a 1, 2 or 3 five times, then rolls a 4, 5 or 6 three times. What is the mean roll value?" Since we do not know exactly how many times each number has been rolled, we need another method to solve this problem. This would be an occasion to use an Assumed Mean. To solve the problem one chooses an arbitrary number which is close to the mean, in this case we could use 6 as the assumed value. Since it is an arbitrary choice, we could also use 5, or 2. It doesn't matter. Next we set up a table as shown below Dice value Frequency (f) Mid-Value (x) d = x - A fd A 1-3 5 2 -4 -20 6 4-6 3 5 -1 -3 8 -23 fd/f A + (fd/f) -2.875 3.125 We find the mid-value of each interval, and subtract the Assumed value (A) in this case 6, then we multiple that value (-4) times the frequency (5) to yield -20. Continue down the table. In the end, you add up your frequencies (8) and your f x d (-23), then divide fd by d. You then add this value to the assumed mean (6 + (-2.875)) and this is your mean 3.125! Easy once you know how.
to find the mean of a set of numbers you have to find the total sum of the data divided by the number of addends in the data.
To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.To find the Z score from the random variable you need the mean and variance of the rv.
No. The null hypothesis is assumed to be correct unless there is sufficient evidence from the sample and the given criteria (significance level) to reject it.
find assumed mean data is 46,55,52,59,63,47,56,50,51,55 ,
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I am 99% sure that it is the guessing average as assumed means, guess, or something like that, and mean means average..so yeah
Differing from standard deviations, the coded deviation method finds the mean of grouped data from the assumed mean using unit deviations. This is a shorter way to find the mean.
In general, you cannot. If the distribution can be assumed to be Gaussian [Normal] then you could use z-scores.
If you mean the throne of England, it was Charles II.
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Because assume places an Ass in front of "U" and "Me"'
Something suggested or assumed as proof for reasoning, discussion or belief.
Something suggested or assumed as proof for reasoning, discussion or belief.
Your question is a bit difficult to understand. I will rephrase: In hypothesis testing, when the sample mean is close to the assumed mean of the population (null hypotheses), what does that tell you? Answer: For a given sample size n and an alpha value, the closer the calculated mean is to the assumed mean of the population, the higher chance that null hypothesis will not be rejected in favor of the alternative hypothesis.
The French meaning is "a tap under the chin." Sobriquet is an assumed name; a nickname.