Direction 2. Continue constructing the table by adding Column 5 Cumulative Frequency with cf Column 6 Cumulative Percentage Frequency with cpf Column 7 Relative Frequency (RF) Direction 3. Continue constructing the table. 1.1 Add column fXi 1.2 Compute for the mean, the median, and the mode of the given data. Sho
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.
Hi! The question is in bold/underlined. The answers in Direction 1 is also attached for reference. Thank you!
Direction1. Construct a Frequency Distribution Table for the above-given data.
1.1 Provide the title for the table and write 1 as the table number.
1.2 Fill-in Column 1 Class Interval. Use 10 class intervals.
Column 2 Class Boundaries
Column 3 Class Marks
Column 4 Frequency
1.3 Show solutions for finding the
mark.
Direction 2. Continue constructing the table by adding
Column 5 Cumulative Frequency with <cf and >cf
Column 6 Cumulative Percentage Frequency with <cpf and >cpf
Column 7 Relative Frequency (RF)
Direction 3. Continue constructing the table.
1.1 Add column fXi
1.2 Compute for the mean, the
Show your solutions.
1.3 Interpret the results.
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