The accuracy of a coin-counter machine is gauged to accept nickels with a mean diameter of millimeters 21.21 mm. A sample of 40 nickles was drawn from a reported defective coin-counter machine located near a school. The sample had a sample mean of 21.213 mm and sample standard deviation 0.01 mm. Test the claim that the mean nickel diameter accepted by this coin-counter machine is greater than 21.21 mm. Test at the 0.01 significance level. (a) Identify the correct alternative hypothesis Ha: Ομ= 21.21 Ομ> 21.21 Ομ< 21.21 Give all answers correct to 4 decimal places. (b) The test statistic value is: (c) Using the Traditional method, the critical value is: (d) Based on your answers above, do you: Fail to reject Ho O Reject Ho (e) Explain your choice in the box below. (f) Based on your work above, choose one of the following conclusions of your test: O There is not sufficient evidence to support the claim O There is sufficient evidence to warrant rejection of the claim O The sample data supports the claim O There is not sufficient evidence to warrant rejection of the claim
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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