5.54 1.88 25.31 7.31 13.90 5.82 2.61 3.95 192.84 17. 40 25.19 7.45 10.15 15.58 2.66 4.33 84.66 15.42 25.79 6.23 25.86 12.03 20.28 4.61 33.46 13.03 20.74 6.44 Skipped 9.10 8.15 8.94 4.79 1.22 4.33 3.71 0.93 4.79 4.56 1.29 2.06 picture Click here for the Excel Data File (a) Select the correct histogram for the above data. Histogram A Histogram B Histogram C Histogram 40 Histogram 35 40 Histogram 30 35 40 25 30 35 20 25 30 15 20 10 15 5 10 15 160 180 Compensation 160 180 Compensation 160 180 Compensation Histogram A Histogram B Histogram C (b) Describe the shape of the histogram. O The distribution is symmetric. O The distribution is skewed to the left. O The distribution is skewed to the right. (c) Identify any unusual values. (Round your answers to 2 decimal places.) Unusual values million million Percent Percent Percent
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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