Chapter 7: The Distribution of Sample Means. Frequency of Scores 0 213456789 1 2 Scores Frequency.

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Presentation transcript:

Chapter 7: The Distribution of Sample Means

Frequency of Scores Scores Frequency

Distribution of Sample Means The distribution of sample means is the collection of sample means for all the possible random samples of a particular size n that can be obtained from a population.

Sampling Distribution A sampling distribution is a distribution of statistics obtained by selecting all the possible sample of a specific size from a population.

Table (samples, score, means) ScoresSample Mean SampleFirstSecondX

Frequency of sample means Sample Means Frequency

Central Limit Theorem For any population with mean µ and standard deviation , the distribution of sample means for sample n will approach a normal distribution with a mean of µ and a standard deviation as n approaches infinity.

The distribution of sample means will be almost perfectly normal if either of the following is true: 1.The population from which the samples are selected is a normal distribution. 2.The Number of scores (n) in each sample is relatively large, around 30 or more.

The mean of the distribution of the sample means will be equal to µ (the population mean) and is called the expected value of x Mean of all the sample means Mean of all the scores in the population

The standard deviation of the distribution of sample means is called the : Standard error of X Standard error = (standard distance between X and µ)

Standard error determined by 2 characteristics: 1.Variability of the population from which the sample came 2.The size of the sample

Law of Large Numbers The larger the sample size (n), the more probable it is that the sample mean will be close to the population mean.

Probability and Distribution of means X µ z

Normal curve of means 20 40% X z

Graph with grid lines µ

Sample Size and Sampling Error Assume a population with a mean of 50 and a standard deviation of 15

Means presented in a table GroupnMeanSE Control Experimental

Group A vs. Group B bar graph Group A Group B X score ( + SE)

Group A vs. Group B line graph Trials X number of mistakes ( + SE) Group A Group B

Comparison of curves A, B, and C µ a µ b µ c Column B p = Column C p =

IQ Scores µ = ?   = 15 X

Given a population of test scores that is normally distributed with µ = 60 and  = 8 I randomly select a test score. What is the probability that the score will be more than 16 points away from the mean? –(Hint : What proportion of test scores are > 76 or < 44 ?)