Qualitative data: categorial
1) Bar chart
2) Pareto : used to represent a frequency distribution for categorial variable displayed by bars
3) Pie chart : circle that is divided into sections according to percentage of frequencies in each
category
Quantitative data : discrete , ungrouped
1) Histogram : displays data by using vertical bars of various heights to represent frequencies
2) Ogive : represents the cumulative frequencies for the classes in a frequency distribution
3) Steam & leaf : uses part of a data value as the stem and part as the leaf to form groups
4) Time series graph : represents data occurring over a specific period of time
5) Frequency Polygon : displays the data by using lines that connect points plotted for the
frequencies at midpoints of the classes
Purpose: to convey data to view in pictorial form
Grouped : has boundaries
Histograms:
- may be used for large data sets
Midpoint : max + min / 2
Class boundary: minus 0.5 in first number add 0.5 in second
Categorial frequency distributions:
- used when data can be placed in specific categories such as nominal or ordinal levels
example:
- political affiliations
- major field of study
- color
- blood type
Ungrouped frequency distributions:
- when we have a few distant numerical data to organize, is in raw form
Grouped frequency distributions:
- when we need to organize large amounts of data, is in raw form, but turns to classes
Classes: subintervals where data is grouped
Reasons for constructing frequency distributions
- to organize the data in a meaningful, intelligible way
- to enable the reader to make comparisons among different data sets
- to facilitate computational procedures for measures of average and spread
- to enable the reader to determine the nature or shape of the distribution
- to enable the researcher to draw charts and graphs for the presentation of data
Scatter Plot:
- graph of ordered pairs of data values that is used to determine if a relationship exists between
two variables
Analyzing a Scatter Plot
- A positive linear relationship exists when the points fall approximately in an ascending straight
line and both the x and y values increase at the same time.
- A negative linear relationship exists when the points fall approximately in a straight line
descending from left to right.
- A nonlinear relationship exists when the points fall along a curve.
- No relationship exists when there is no discernable pattern of the points
1) Bar chart
2) Pareto : used to represent a frequency distribution for categorial variable displayed by bars
3) Pie chart : circle that is divided into sections according to percentage of frequencies in each
category
Quantitative data : discrete , ungrouped
1) Histogram : displays data by using vertical bars of various heights to represent frequencies
2) Ogive : represents the cumulative frequencies for the classes in a frequency distribution
3) Steam & leaf : uses part of a data value as the stem and part as the leaf to form groups
4) Time series graph : represents data occurring over a specific period of time
5) Frequency Polygon : displays the data by using lines that connect points plotted for the
frequencies at midpoints of the classes
Purpose: to convey data to view in pictorial form
Grouped : has boundaries
Histograms:
- may be used for large data sets
Midpoint : max + min / 2
Class boundary: minus 0.5 in first number add 0.5 in second
Categorial frequency distributions:
- used when data can be placed in specific categories such as nominal or ordinal levels
example:
- political affiliations
- major field of study
- color
- blood type
Ungrouped frequency distributions:
- when we have a few distant numerical data to organize, is in raw form
Grouped frequency distributions:
- when we need to organize large amounts of data, is in raw form, but turns to classes
Classes: subintervals where data is grouped
Reasons for constructing frequency distributions
- to organize the data in a meaningful, intelligible way
- to enable the reader to make comparisons among different data sets
- to facilitate computational procedures for measures of average and spread
- to enable the reader to determine the nature or shape of the distribution
- to enable the researcher to draw charts and graphs for the presentation of data
Scatter Plot:
- graph of ordered pairs of data values that is used to determine if a relationship exists between
two variables
Analyzing a Scatter Plot
- A positive linear relationship exists when the points fall approximately in an ascending straight
line and both the x and y values increase at the same time.
- A negative linear relationship exists when the points fall approximately in a straight line
descending from left to right.
- A nonlinear relationship exists when the points fall along a curve.
- No relationship exists when there is no discernable pattern of the points
