The peak is located in the upper value bars (right side).
A circular statistical graphic divided into slices to illustrate numerical proportions.
Every class has equal frequency.
A distribution shape where both sides are more or less the same when folded vertically down the middle.
They may have slightly different values.
Line Chart.
To organize and summarize data into classes for easier analysis.
The relationship between two variables over a continuous interval.
It has a longer tail on the right side.
Data organized into frequency tables.
SEHH1008.
Mathematics and Statistics for College Students.
SEHH1008.
Donut Chart.
It is symmetrical with bars of the same height.
Mathematics and Statistics for College Students.
It has a large number of occurrences in the lower value bars (left side) and few in the upper value bars (right side).
It indicates that there are two classes with the largest frequencies separated by at least one class.
In the lower value bars (left side).
Both sides of the graph are mirror images of each other.
Grouped Column Chart.
The peak is located in the lower value bars (left side).
It has a longer tail in the upper value bars (right side).
It represents the peak of the distribution.
A type of data visualization that displays three dimensions of data using bubbles.
It may suggest that we are sampling from two different populations.
In the upper value bars (right side).
Two numerical values on the axes and a third value represented by the size of the bubble.
To compare different groups or categories.
In the lower value bars (left side).
Class Width = Largest Data Value - Smallest Data Value.
It has a peak on the right side and a longer tail on the left side.
A graphical representation of two variables plotted along two axes to show their relationship.
52 minutes.
It is the difference between the lower class limit of one class and the lower class limit of the next class.
A graph that displays cumulative frequencies.
Uniform or rectangular.
By observing the pattern of the points, such as whether they form a line or curve.
It remains the same as the computed value.
It is the value computed for each class that represents the center of that class.
The lower value bars (left side).
The longer tail is on the right side.
Upper class boundary and cumulative class frequency.
It indicates a weak or no correlation between the variables.
Draw a line at the middle of the histogram.
Midpoint = (Lower Class Limit + Upper Class Limit) / 2.
16.5 - 24.5.
24.5 - 32.5.
32.5 - 40.5.
7.
9.
Bubble chart, pie chart, grouped column chart, line chart, scatter plot, donut chart, and time series chart.
10.
By subtracting the lower limit of one class from the upper limit of the next class.
60 patients.
60.
3.
To show relationships between three variables in a visually appealing way.
Each slice represents a category's contribution to the total.
In fields like business, economics, and education to compare data points.
Increase the computed value to the next higher value with the same number of decimal places as observed from the data.
Tableau.
Mound-shaped symmetrical.
It partitions data into classes or intervals and shows how many data values are in each class.
Class width = 7.2, rounded to 8.
To ensure that classes accommodate all possible data values from the data set.
So that each data value falls into exactly one class.
Frequencies.
Lower: 9, Upper: 16.
Make a dot over the upper class boundary at the height of the cumulative class frequency.
Each data value should fall into exactly one class.
Round up to the nearest integer.
Connect these dots with line segments.
Relative frequency and cumulative frequency.
8.5 - 16.5.
A cumulative frequency polygon used to represent cumulative frequencies.
About 48 patients (with an error of ± 1 accepted).
To represent the waiting times of 60 patients.
40.5 - 48.5.
52.5.
40.
50 patients.
57 patients.
57.
8.5 – 16.5.
Six classes.
The lowest data value that can fit in a class.
A graphical representation of data points in a time sequence.
Determine the number of classes (5 – 20 classes) and the corresponding class width.
Class width = (Largest data - Smallest data) / Number of classes.
Use the smallest data value as the lower class limit of the first class, then add the class width to get the lower limit of the next class.
Each point represents an observation with values for two different variables.
Class boundaries.
Compute the Class Width using the formula.
PYTHON.
Seasonal patterns and trends in data.
Points that trend upwards from left to right.
Class width is increased to 3.3.
9.
The corresponding class frequency.
The range of values that define each class in a frequency distribution.
They tell us how many data values are smaller than an upper class boundary.
The location of the peak and the longer tail.
To organize raw data.
Histograms and ogives.
9 patients.
8.5 – 16.5.
48.5 - 56.5.
27.
Interpreting information displayed in graphs.
50.
8.
It provides insights into the waiting time patterns.
In the lower value bars (left side).
Microsoft Power BI.
9 minutes.
The highest data value that can fit in a class.
Make a frequency table with the designated number of classes.
Integer data.
SAS FORECASTING.
Data collected at successive points in time.
They can be difficult to interpret when there are many small slices.
In the upper value bars (right side).
It provides the actual values that will be categorized into classes.
Each data class along with the number (frequency) of data in that class.
It extends between the corresponding class boundaries.
Points that trend downwards from left to right.
A distribution with two peaks.
Midpoint (or class mark).
The values that separate classes without forming gaps between them.
Lower: 9, Upper: 16.
Lower: 8.5, Upper: 16.5.
20.5.
The average of the lower and upper class limits.
Choosing appropriate types of graphs.
40 patients.
It helps in determining the range of data within each class.
The lower and upper values that define a class.
40.5 – 48.5.
8 (calculated as 24.5 - 16.5).
40.5 – 48.5.
When you want to show the relative proportions of a whole.
To analyze trends over time.
100% of the data represented.
It has a large number of occurrences in the upper value bars (right side) and few in the lower value bars (left side).
60 patients.
8.
Make a frequency table showing class boundaries and cumulative frequencies.
The longer tail is on the left side.
R Programming / R - Studio.
Time intervals on the x-axis and data values on the y-axis.
The midpoint of each class.
Total the tallies to obtain each class frequency.
The halfway points between the upper limit of one class and the lower limit of the next class.
At the lower class boundary of the first class.
It is the sum of the frequencies for that class and all previous classes.
The lower and upper values that define a class in a frequency distribution.
The values that separate classes, typically extending 0.5 units below and above the class limits.
Basic distribution shapes.
27 patients.
18.
The number of data values that fall into a particular class or category.
40.
The values that separate classes, typically extending 0.5 units beyond the class limits.
60 patients.
18.
