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July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 7 - Sampling Distribution of Means.

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Presentation on theme: "July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 7 - Sampling Distribution of Means."— Presentation transcript:

1 July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 7 - Sampling Distribution of Means

2 July, 2000Guang Jin Key Concepts in This Chapter b Distribution of a population b Distribution of sample means b Central limit theorem b Standard error of the mean b Z score of a sample mean b Student’s t distribution b t score and degree of freedom

3 July, 2000Guang Jin The Distribution of a Population and the Distribution of its Sample Means b A distribution of sample means is the set of values of sample means obtained from all possible samples of the same size (n) from a given population. b A distribution of a population includes a set of intervals and displays their frequency (numbers of cases or occurrences) in each intervals for that given population.

4 July, 2000Guang Jin Central Limit Theorem b The central limit theorem states that for a randomly selected sample of size n (n  25, but the larger n is, the better the approximation) with a mean of  and standard deviation  : The distribution of sample means is approximately normal regardless of whether the population distribution is normal or not

5 July, 2000Guang Jin Central Limit Theorem (Cont’d) The mean of the distribution of sample means is equal to the mean of the population distribution - that is, The standard deviation of the distribution of sample means is equal to the standard deviation of the population (  ) divided by the square root of the sample size (n), that is,

6 July, 2000Guang Jin Standard Error of the Mean b The standard deviation of the sample means, referred to as the standard error of the mean, is denoted as SE( ), that is, b SE ( ) is a rough measure of the average amount by which sample mean deviate from population mean (amount of sampling error).

7 July, 2000Guang Jin In practice, the standard error of the mean is calculated by: b Where: S - sample standard deviation - standard error of the mean estimated from a sample

8 July, 2000Guang Jin Z score of a sample mean b Z score of a sample mean establishes the relative position of in a distribution of sample means and can be calculated by:

9 July, 2000Guang Jin Student’s t distribution b When sample standard deviation is used to calculate z score of a sample mean, we no longer have the standard normal distribution, instead we have so called Student’s t distribution b t distribution is similar to the standard normal distribution and approximate standard normal distribution when sample size exceeds 30.

10 July, 2000Guang Jin t score and degree of freedom b The equation for t score is: b Degree of freedom (df) can be calculated by:


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