Consider the data set given in the accompanying table. Complete parts (a) through (d). E Click the icon to view the data table. Marginal distribution 210 80 30 100 (b) Construct a relative frequency marginal distribution. Relative frequency X2 X3 marginal distribution y1 50 15 50 Data Table y2 30 15 50 Relative frequency marginal distribution (Round to three decimal places as needed.) 1 X2 X3 (c). Construct a conditional distribution by x. y1 50 15 50 X2 X3 Y2 30 15 50 Y2 Print Done Total 1 1 (d) Draw a bar graph of the conditional distribution found in part (c). Let the blue (left) bars represent the conditional distribution of y, and let the red (right) bars represent
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.
Given joint frequency distribution of x and y. We need to find relative frequency marginal distributions of x and y.
And also the conditional distributions of x.
| X1 | X2 | X3 | |
| Y1 | 50 | 15 | 50 |
| Y2 | 30 | 15 | 50 |
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