Exercises 6.1-6.9 6.5 Understanding the Principles 6.1 What is the difference between a population parameter and a sample statistic? 6.2 What is a sampling distribution of a sample statistic? Learning the Mechanics 6.3 The probability distribution shown here describes a pop- ulation of measurements that can assume values of 0, 2, 4, and 6, each of which occurs with the same relative frequency: NW 4 6. p(x) 1/4 1/4 1/4 1/4 a. List all the different samples of n = that can be selected from this population. b. Calculate the mean of each different sample listed in 2 measurements part a. c. If a sample of n = lected from the population, what is the probability that a specific sample will be selected? d. Assume that a random sample of n = is selected from the population. List the different values of x found in part b, and find the probability of each. Then give the sampling distribution of the sample mean x in tabular form. e. Construct a probability histogram for the sampling dis- tribution of x. 2 measurements is randomly se- 2 measurements
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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