FREQUENCY DISTRIBUTION in Basic Statistics with clear samples.ppt

A frequency distribution is the pattern of frequencies of a variable. It’s the number of times each possible value of a variable occurs in a dataset.

1. DESCRIPTIVE
STATISTICS
CHAPTER 3

2. TOPICS DISCUSSED IN THIS CHAPTER
1. Frequency Distributions
2.Data Presentations: tables and graphs in APA format
measures of Distribution
•Central Tendency
•Relative Position
•Variability and Shape

3. FREQUENCY
DISTRIBUTION
PRESENTED BY:
JOVIE I. DELGADO

4. DESCRIPTIVE STATISTICS
*Is a branch of statistics that aims to summarize
and display the main features of data set using
numerical measures, tables, and graphs
* Intent is to describe the data that actually
collected before performing any inferential
analysis, such as hypothesis testing or regression.

5. •Frequency of a value is the number of times it
occurs in a dataset.
•Way of organizing data that displays the number (or percent)
of individuals that obtained a particular score or fell in a
particular category
•Presented in a table or a graph.
•Help us understand the distribution of values in the
data.
•Used to get “picture” of how scores were distributed.
FREQUENCY DISTRIBUTION

7. Four types of Frequency Distributions
•Ungrouped frequency distributions : The
number of observations of each value of a
variable.
•You can use this type of frequency
distribution for categorical variables.
•Grouped frequency distributions : The
number of observations of each  class
interval of a variable. Class intervals are
ordered groupings of a variable’s values.
•You can use this type of frequency
distribution for quantitative variables.

8. •Relative frequency distributions: The proportion of
observations of each value or class interval of a
variable.
•You can use this type of frequency distribution
for any type of variable when you’re more
interested in comparing frequencies than the
actual number of observations.
•Cumulative frequency distributions: The sum of the
frequencies less than or equal to each value or class
interval of a variable.
•You can use this type of frequency distribution
for ordinal or quantitative variables when you
want to understand how often observations fall
below certain values.

9. How to make a frequency table?
Frequency distributions are often displayed
using frequency tables. A frequency table is an
effective way to summarize or organize a
dataset.
It’s usually composed of two columns:
•The values or class intervals
•Their frequencies

10. The method for making a
frequency table differs between
the four types of frequency
distributions. You can follow
the guides below or use
software such as Excel, SPSS, or
R to make a frequency table.

19. How to graph a frequency
distribution?
Pie charts, bar charts, and histograms
are all ways of graphing frequency
distributions.
The best choice depends on the type of
variable and what you’re trying to
communicate.

21. BASIC TYPES OF GRAPHS
(1)bar graphs
(2)histograms
(3)line graphs
(4) pie graphs

22. Bar graph the bars do not touch while
the bars do touch in a histogram.

23. Bar graphs are used when the data are discrete or
qualitative. The space between the bars of a bar
graph emphasize that there are no possible values
between any two categories.
When the data are continuous, we use a
histogram, to indicate that there are possible
values between any two categories.

24. Line graphs can be used whenever a
histogram is appropriate

25. Pie chart is a type of graph that represents
the data in the circular graph.
The slices of pie show the relative size of the
data. It requires a list of categorical
variables and numerical variables.
The term “pie” represents the whole, and
the “slices” represent the parts of the
whole. 

26. The pie chart is an important
type of data representation. It
contains different segments
and sectors in which each
segment and sector of a pie
chart forms a specific portion
of the total(percentage). The
sum of all the data is equal to
360°.
The total value of the pie is
always 100%.

28. To work out with the percentage for a pie chart,
follow the steps given below:
•Categorize the data
•Calculate the total
•Divide the categories
•Convert into percentages
•Finally, calculate the degrees
Therefore, the pie chart formula is given as
(Given Data/Total value of Data) × 360°

29. THANK YOU ALL FOR
LISTENING.