Please put the following in an actual formula: d) Step 4: Sample score on comparison distribution Lower limit of acceptance region 2 - 1.96*s = 20 - 1.96*
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.
Please put the following in an actual formula:
d) Step 4: Sample score on comparison distribution
Lower limit of acceptance region 2 - 1.96*s = 20 - 1.96*1.107 = 20 - 2.17 = 17.83
Upper limit of acceptance region 2 +1.96*s = 20 + 1.96*1.107 = 20 + 2.17 = 22.17
Here, only the lower acceptance limit is relevant
d)
Given Lower limit of acceptance region 2 - 1.96*s = 20 - 1.96*1.107 = 20 - 2.17 = 17.83
Actual formula for lower limit is,
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