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:star: Descriptive Statistics :star: - Coggle Diagram
:star: Descriptive Statistics :star:
Data Collection
Qualitative Data
Nominal Data
Ordinal Data
Quantitative Data
Discrete Data
Continuous Data
Organizing Data
Raw Data
Data Array
Data Presentation
Frequency Distribution
Class Interval and Class limit
example: 900-999. There is also a term called lower and upper class limit
Class Boundary
If the number are between 900-999. Then the boundary or the true class limit are 888.5 and 999.5
Width of Interval Class
The width of interval class is actually the subtraction between the lower and upper class boundaries (C).
Class midpoint or Class mark
Class midpoint are gathered from the addition of the upper and lower class boundaries, then the result are divided by 2
Considerations in preparing the frequency distribution
All the data need to be listed, each units only listed once in one class.
Each width of class need to be the same, usually the multiple of 5
Open class interval are the priority
if possible, the class interval is selected so that the middle value equals the actual concentrated data value
Graphic Presentation
Histogram
Poligon :Frequency
Cumulative frequency distribution
Frequency Curve
The Sample Mean and Median
Sample Mean
Sample Median
Trimmed Means
Trimming away a certain percent on both the largest and smallest values
Measures of Variability
Sample Variances
Sample Standard Deviation
Simply just the root of S
Standard Deviation and Variance
variance is a measure of the
average squared deviation from the mean ¯x
Scatter Plot
Stem-and-Leaf Plot
Box-and-Whisker Plot or Box Pl
This plot encloses the interquartile range of the data in a box
that has the median displayed within
Moment
Skewness
Kurtosis
is the degree of flat or a peak of a curve of a distribution relative to the normal distribution. The high peaks are called leptokurtic, and the flat ones are called flat topped
the degree of asymmetry or deviation from the symmetry of a distribution. Depicted by a polygon curve, it can be positive skewness or vice versa, negative skewness. Using the formula:
