Sample Mean for a Normal Population

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• 13 Probability Statements: True or False?

  If a sample of at least 30 scores is randomly selected from a normal population, the sample mean will be equal to the population mean. 6.

• distribution of sample means, deviation, sample size, random selection

  For a population with a mean of µ =50 and a standard deviation of Ï? = 10, how large a sample mean (M) and the population mean for: a. sample of n= 4 scores b. a sample of n = 16 scores c. a sample of n =25 scores 10.

• Probability based on normal distributio and CLT

  A random sample of n = 4 scores is obtained from a normal population with  = 20 and  = 4. What is the probability of obtaining a mean greater than M = 22 for this sample?

• Probability: Normal Distribution and The Central Limit Theorem

  c) Draw a dot plot for the sampling of the sample mean for the sample size of three. d) For a random sample size 3. What is the chance that the sample mean will equal the population mean.

• Multiple choice questions

  If a random sample of n cases is drawn from a population with mean  and standard deviation  , then the sampling distribution of the mean (the distribution of all possible means for samples of size n) 1) has a mean equal to the population

• Central Limit Theorem of Mean

  A sample needs not to be very large for sampling mean distribution to behave like a normal distribution. Statistician use normal distribution as an approximation to sample mean distribution whenever sample size is at least 30.

• What would be the mean, variance, standard deviation and shape of the distribution of sample means?

  If many samples of size 15 (that is, each sample consists of 15 items) were taken from a large normal population with a mean of 18 and variance of 5, what would be the mean, variance, standard deviation and shape of the distribution of sample means?

• Distribution of the difference of two sample means.

  means have normal distributions with a known mean and known variances.

• Multiple choice -normal distribution, Central Limit Theorem

  a. for a large n, it says the population is approximately normal. b. for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size.