Bimodal Distribution

By Author: Sherry Roberts
Total Articles: 81
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Question #1: Explain the following key term in Chapter 4 and Chapter 5
A. Bimodal Distribution; refers to a continuous probability distribution that has two different modes that appear as different peaks when graphically represented
B. Mode; refers to a set of values that appear most frequently
C. Median; is measure of central tendency and the value at the middle of data observations for old observation or average of two middle values for even observations, when arranged from smallest to largest value
D. Mean; it is also known as average that shows central tendency by adding all data observations or populations and dividing them by number of observations or population
E. A measure of Central Tendency; refers to a single value that explains how a group of data cluster around the central value. It describes center of data using three measures namely mean, median and mode
F. Outlier; refers to a point appearing and falling more than 1.5 times in inter-quartile range, above the third quartile or below the first quartile
G. Skewed Distribution; refers to a measure of the asymmetric ...
... probability distribution of real data values regarding the mean. It is positive, negative or undefined
H. Measures of Dispersion; it is also known as variability, scattering, or spreading of values. It is extent in which data is distributed based on how it is stretched or squeezed. Measure of dispersion includes variance, standard deviation, and interquartile range
I. Deviation; refers to statistical deviation or measure of differences between observed value of variables as well as other values referred to as variable means.
J. Range; the range is applied to a set of data and information and is the difference between largest and smallest value. It can also be used as the smallest interval where the all data is located. It provides indicators of how data is statistically dispersed
K. Standard Deviation; it is a measure used to reveal dispersion or variation of items in distribution. It is determined by square root of arithmetic means of squares of deviations from arithmetic means
L. Variance; it is expected an of squared deviation of a set of random values of variables from the mean. It measures the far a set of values of variables are spread from mean
M. Interquartile Range; it is abbreviated as (IQR). It measures variability or dispersion by dividing sets of data into quartiles. Quartiles divide a ranked order of a set of data into four parts. Values that indicate divisions are called first second and third quartile denoted as Q1, Q2, and Q3 respectively
N. Variation Ratio; it refers to a simple measure of statistical dispersion in nominal distribution. It is a simple to measure of qualitative variation. It is a proportion of cases outside mode categories also referred to as instance of data
Question #2: Determine the measure of central tendency
Which measure of central tendency do you think best summarizes the central tendency of these data in the following table, and explain why?
The mode is the best measure of central tendency. It reveals the real distribution of hate based on a particular aspect of life
Question #3: Determine the median
Median position is 3, 4, 4, 5,5,5,7,8,10,11,15 = 5
Question #4: Determine the median for the grouped data
Use the following table and statistics to find the median number of “time-until-rearrest” among 12 inmates in the study and describe, in detail, the process of determining the median number.
Question #5: Determine the mean
Use the following table and statistics to find the mean number of “response times to 911 calls for police assistance” in the study and describe, in detail, the process of determining the mean.

Sherry Roberts is the author of this paper. A senior editor at Melda Research in online nursing papers. If you need a similar paper you can place your order for a custom research paper from legitimate research paper writing service services.