TATISTICAL GRAPHS
These are the graphs designed to illustrate values of geographical items by means of lines or bars and in turn allow quantitative analysis.
The most useful statistical graphs for the illustration of values include the following.
- Line graphs
- Bar graphs
- Combined bars and line graph
LINE GRAPHS
These are the graphs which use line (s) to illustrate the values of items to give quantitative analysis.
Any line graph has two axes of the following:-
-X – axis; This is also known as the base or horizontal axis. It is used principally to show the value of independent variable like date or places.
-Y – axis: This is also known as the vertical axis. It is used show the values for the dependent variable of like output of crops, minerals etc.
TYPES OF LINE GRAPHS
Linear graphs are extremely varied. They are differently deigned to meet varied functions (roles). With respect to this consideration, linear graphs recognized to be of the following forms:
- Simple line graph
- Cumulative line graph
- Divergent line graph
- Group line graph
- Compound line graph
Simple line graph
It is a form of line graph, designed to have one line to illustrate the values of one item in relation to dependent and independent variables. i.e. It is designed to show the values of one item per varied date or places.
CONSTRUCTION OF THE SIMPLE LINE GRAPH
Consider the given hypothetical data below showing maize production for country X in 0,000 metric tons (1990 – 1995).
| YEAR | PRODUCTION |
| 1990 | 100 |
| 1991 | 250 |
| 1992 | 300 |
| 1993 | 150 |
| 1994 | 500 |
| 1995 | 400 |
Procedure
(a) Variables identification
Dependent variable ….. production values
Independent variable ….. Date (Years).
Y – axis …… production values
X – axis ……. Years
(b) Vertical and horizontal scales estimation
Hence; VS is 1 cm to 50000 tons.
Horizontal scale is up on decision
Hence; 1cm represents 1 year
MAIZE PRODUCTION FOR COUNTRY X IN (0,000) Metric tons
Scales:
VS: 1 cm to 50 tons
HS: 1cm to 1 year
Source:
Hypothetical data
Strengths of the simple line graph
It is much easier to prepare as it involves to complicated mathematical works, and also a single line establishes the graph.
From the graph, the absolute values are extracted
It is comparatively easier to read and interpret the values
It has perfect replacement by simple bar graph
Setbacks of the simple line graph
It is a limited graphical method as only suited to represent the value for one item.
Sometimes it becomes difficult to assess the vertical scale if the variation between the highest and lowest values appear wider enough.
Cumulative line graph
It is a form of line graph designed to show the accumulated total values at various dates or possibly places for a single item. This graphical method has no alternative graphical bar method as it can be compared to other linear graphical methods.
Construction of the cumulative line graph
Consider the given hypothetical data below showing maize production for country X.
| YEAR | PRODUCTION |
| 1990 | 50 |
| 1991 | 40 |
| 1992 | 90 |
| 1993 | 100 |
| 1994 | 90 |
| 1995 | 130 |
Procedure
(a) Variables identification
- Dependent variable ……….. production values
- Independent variable —- Date (Years)
Y – axis ………. Production values
X – axis …………Years
(b) Vertical and horizontal scales estimation
(c) Determination of the cumulative values.
| YEAR | PRODUCTION | CUM VALUES |
| 1990 | 50 | 50 |
| 1991 | 40 | 90 |
| 1992 | 90 | 180 |
| 1993 | 100 | 280 |
| 1994 | 90 | 370 |
| 1995 | 130 | 500 |
Hence: VS; 1cm represents 50 tons
Thus; the cumulative lien graph appears as follow.
Cumulative line graph: Maize production for country X.
SCALE:-
VS….. 1cm represents 50 tons
HS ….. 1cm represents 1 year
Source ….. Hypothetical data.
Merits of the cumulative line graph
The graphical method shows cumulative values
From the graph the values can be revealed and quantitatively analyzed
Setbacks of the cumulative line graph
The graphical method is not suited to show cumulative values for more than one item, it is thus; the graphical method limited for showing the values of a single item.
It needs high skill to reveal the actual values of the item represented
It has no alternative graphical bar method.
Divergent line graph
It is a form of line graph designed to illustrate the increase and decrease of the distribution values in relation to the mean. The graph is designed to have upper and lower sections showing positive and negative values respectively.
The two portions are separated by the steady line graduated with zero value along the vertical line. The steady line also shows the average of all values.
Construction of the divergent line graph
Consider the following tabled data which show export values of coffee for country X in millions of dollars
| YEAR | EXPORT VALUES (000,000 dollars) |
| 1952 | 345 |
| 1953 | 256.5 |
| 1954 | 283 |
| 1955 | 500 |
| 1956 | 335 |
| 1957 | 330.5 |
(a) Variables identification
- Dependent variable ……….. Export values
- Independent variable —- Date (Years)
Y – axis ………. Export values
X – axis …………Years
(b) Computation of the arithmetic mean
345 + 256 + 283 + 300 + 335 + 330.5 = 1850
Then;
Computation of the deviation values
1952 345-308 = 37
1953 256.5 – 308 = 52.5
1954 283-308 = -25
1955 300 – 308 = -8
1956 335 – 308 = 27
1957 330.5 – 308 = 22.5
(c) Estimation of the vertical scale.
Thus: the vertical scale
1cm represents 15 or -15 million dollars
(d) The graph has to be redrawn accordingly as follows:-
Source:-
Hypothetical data
Scales:-
Vertical scale 1cm represents 15 or 15 tons
Horizontal scale 1cm represents 1 year
Merits of the divergent line graph
The graphical method is useful for showing increase and decrease of the values.
The graphical method shows the average of all values
It has perfect replacement by divergent bar graph
Setbacks of the divergent line graph
The graphical method is not suited to show the increase and decrease values for more than one items, it is thus; the graphical method is limited to a single item.
It needs high skill to reveal the actual values of the item represented.
It is time consuming graphical method as its preparation involves a lot of mathematical works.
It requires high skill to construct the divergent line graph.
Group line graph
It is a form of statistical line graph designed to have more than one lines of varied textures to illustrate the values of more than one items. Group line graph is alternatively known as composite, comparative, and multiple line graph.
Construction of the group line graph
Consider the given data below showing values of export crops from Kenya (Ksh Million).
| Crop/Year | 1997 | 1998 | 1999 | 2000 | 2001 |
| Tea | 24,126 | 32,971 | 33,065 | 35150 | 34,448 |
| Coffee | 16,856 | 12,817 | 12,029 | 11,707 | 7,460 |
| Horticulture | 13,752 | 14,938 | 17,641 | 21,216 | 19,846 |
| Tobacco | 1,725 | 1,607 | 1,554 | 2,167 | 2,887 |
(a) Variables identification
Dependent variable …… export values
Independent variable …. Date (years)
Y – -axis………. export values
X – axis………..Years
(b) Verticals identification
Dependent variable……..export values
Independent variable …… Date (Years)
Hence; VS 1cm represents 5000 export value
Thus; the group line graph appears as follows:-
KENYA: CROPS EXPORT VALUES
Scales:-
Vertical scale: 1cm to 5,000 export values
Source: Kenya Economic Survey 1969
Strengths of the group line graph
It is much easier to prepare as it involves no complicated mathematical works
It is useful graphical method for showing the values of more than one cases.
From the graph, the absolute values are extracted as the values directly shown
It is comparatively easier to read and interpret the values.
It has perfect replacement by group bar graph.
Setbacks of the group line graph
Some times; it becomes difficult to assess the vertical scale if the variation between the highest and lowest values appears wider enough
Crossing of the lines on the graph may confuse the interpreter.
A problem may arise in the selection of the varied line textures.
Compound line graph
It is a line graph designed to have more than one lines compounded to one another by varied shade textures to show the cumulative values of more than one items.
Construction of the compound line graph
Consider the given data below showing cocoa production for the Ghana provinces in 000 tons.
| YEAR/PROV | TV Togoland | E. province | W. province | Ashanti |
| 1947/48 | 40 | 40 | 30 | 35 |
| 1948/49 | 50 | 60 | 45 | 100 |
| 1949/50 | 45 | 46 | 89 | 110 |
| 1950/51 | 45 | 47 | 44 | 124 |
| 1951/52 | 47 | 23 | 50 | 100 |
| 1952/53 | 51 | 14 | 57 | 118 |
Procedure
(a) Variables identification
Dependent variable…… export values
Independent variable ….. Date (Years)
Y – -axis……….export values
X – axis………..Years
(b) Cumulative values determination for the dates.
1947/48 40+40+30+35 = 145
1948/49 50+60+45+100 = 225
1949/50 45+46+89+110 = 290
1950/51 45+47+44+124 = 260
1951/52 47+23+50+100 = 220
1952/53 51+14+57+118= 240
(c) Vertical and horizontal scales determination
Hence; The vertical scale, 1cm represent 50 tons
Thus the graph appear as follow:-
Strengths of the compound line graph
It is useful graphical method for showing the cumulative values of more than one case.
Depending on the skill the interpreter has, from the graph, the absolute values are extracted as the value directly shown.
It has perfect replacement by compound bar graph
It is comparatively easier to assess the vertical scale to be used.
Setbacks of the compound line graph
It needs high skill to interpret the graph
It needs high skill to construct the graph
A problem may arise in the selection of the varied line textures.
BAR GRAPHS
These are the graphs which use bars to illustrate the values of items to give quantitative analysis.
Any bar graph has two axes
-X-axis; This is also known as the base or horizontal axis. It is used principally to show the values of independent variable like date or places.
– Y – axis; This is also known as the vertical axis. It is used show the values for the dependent variable of like output of crops, minerals etc.
TYPES OF BAR GRAPHS
Like line graphs, bar graphs are also extremely varied as differently designed to meet varied functions. With respect to this consideration, bar graphs categorized into the following:-
- Simple bar graph
- Divergent bar graph
- Group bar graph
- Compound bar graph
- Percentage bar graph
- Population pyramid
Simple bar graph
It is a form of bar graph, designed to have bars of similar texture to illustrate the values of one item in relation to dependent and independent variables. i.e. It is designed to show the values of one item per varied date or places.
Construction of the simple bar graph
Consider the given data below showing cocoa purchase by areas, in 000 metric tons (1953)
| Province | Purchase |
| Ashanti | 104 |
| W-Province | 39 |
| E-Province | 45 |
| TV Togo land | 22 |
Procedures
(a) Variable identification
Dependent variable …… Purchase
Independent variable …. Provinces
Y – -axis………purchase values
X – axis………..Provinces
(b) Verticals identification
Dependent variable……..export values
Independent variable …… Date (Years)
Thus; the vertical scale: 1cm represents 20,000 tons.
Bar width – 1cm
Bar space = 0.5 cm
The graph has to be constructed accordingly.
COCOA PURCHASE BY PROVINCES (1953/54
Vertical scale; 1cm represents 20000 tons.
Strengths of the simple bar graph
It is much easier to prepare as it involves no complicated mathematical works, and also bars of similar texture established in the graph.
From the graph, the absolute values are extracted.
It is comparatively easier to read and interpret the values
It has perfect replacement by simple line graph.
Setbacks of the simple bar graph
It is a limited graphical method as only suited to represent the values for one item
Some times; it becomes difficult to assess the vertical scale if the variation between the highest and lowest values appear wider enough.
Divergent bar graph
It is a form of bar graph designed to illustrate the increase and decrease of the distribution values in relation to the mean. The graph is designed to have upper and lower sections showing positive and negative values respectively.
The two portions are separated by the steady lien graduated with zero value along the vertical line. The steady lien also shows the average of all values.
Construction of the divergent line graph
Consider the following tabled data which show export values of coffee for country X in millions of dollars.
| YEAR | EXPORT VALUES (000,000 dollars) |
| 1952 | 345 |
| 1953 | 256.5 |
| 1954 | 283 |
| 1955 | 300 |
| 1956 | 335 |
| 1957 | 330.5 |
(a) Variable identification
Dependent variable …… Export values
Independent variable …. Date (Years)
Y – -axis………. Export values
X – axis………..Years
(b) Computation of the arithmetic mean
345 + 256 + 283 + 300 + 335 + 330.5 + 1850
(c) Computation of the deviation values
1952 345 – 308 = 37
1953 256.5 – 308 = 52.5
1954 283 – 308 = -25
1955 300 – 308 = -8
1956 335 – 308 = 27
1957 330.5 – 308 = 22.5
(d) Estimation of the vertical scale
Thus: the vertical scale 1cm represents 15 or –15 million dollars
Bar width – 1cm
Bar space – 1cm
(e) The graph has to be redrawn accordingly as follows.
COFFEE EXPORT VALUES FOR COUNTRY X
In million dollars
Scales:-
Vertical scale 1cm represents 15 or – 15 tons
Horizontal scale: 1cm represents 1 year
Source:- Hypothetical data
Merits of the divergent bar graph
The graphical method is useful for showing increase and decrease of the values
The graphical method shows the average of all values
It has perfect replacement by divergent line graph.
Setbacks of the divergent bar graph
The graphical method is not suited to show the increase and decrease values for more than one item, it is thus; the graphical method is limited to a single item.
It needs high skill to reveal the actual values of the item represented.
It is time consuming graphical method as its preparation involves a lot of mathematical work.
It requires high skill to construct the divergent bar graph.
Grouped bar graph
It is a form of statistical bar graph designed to have more than one bars of varied textures to illustrate the values of more than one items.
Grouped bar graph is alternatively known as composite, comparative, and multiple bar graph.
Construction of the group bar graph
Consider the given data below for cocoa purchase by provinces in Ghana (1947/48 – 1950/51)
| YEAR/PROV | TV Togoland | E. province | W. province | Ashanti |
| 1947/48 | 20 | 54 | 28 | 106 |
| 1948/49 | 26 | 80 | 46 | 126 |
| 1949/50 | 24 | 67 | 40 | 116 |
| 1950/51 | 22 | 72 | 45 | 123 |
(a) Variables identification
Dependent variable…… purchase values
Independent variable ….. Date
Y – -axis……… .purchase values
X – axis………..Date
(b) Vertical scale estimation
Hence; Vs, 1cm to 20,000 tons
Bar width = 1cm
Bar space = 1cm
(c) The graph should be drawn accordingly.
COCOA PURCHASE BY PROVINCES (1953/54)
Strengths of the grouped bar graph
It is much easier to prepare as it involves no complicated mathematical works
It is useful graphical method for showing the values of more than one cases.
From the graph, the absolute values are extracted as the value are directly shown
It is comparatively easier to read and interpret the values.
It has perfect replacement by group line graph.
Setbacks of the grouped graph
Some times; it becomes difficult to assess the vertical scale if the variation between the highest and lowest values appear wider enough.
A problem may arise in the selection of the varied bar textures.
Compound Bar graph
It is a bar graph designed to have bars divided proportionally showing the cumulative values of more than one items per varied dates or places
Compound bar graph is alternatively known as divided bar graph, or superimposed bar graph.
Construction of the compound bar graph
Consider the given data below showing cocoa production for the Ghana provinces in 000 tons.
Consider the given data below showing cocoa purchase by provinces (1947/48 to 1950/51)
| REGION/YEAR | 1947/48 | 1948/49 | 1949/50 | 1950/51 |
| Ashanti | 106,000 | 126,000 | 116,000 | 123,000 |
| W.province | 28,000 | 46,000 | 40,000 | 45,000 |
| E.Province | 54,000 | 80,000 | 67,000 | 72,000 |
| T.Volta | 20,000 | 26,000 | 24,000 | 22,000 |
Procedure
(a) Variable identification
Dependent variable ….. export values
Independent variable … Date (Years).
Y – -axis………. purchase values
X – axis………..Years
(b) Cumulative values determination for the dates.
1947/48……….. 106,000 + 28,000 + 54,000 + 20,000 = 208
1948/49………… 126,000 + 46,000 + 80,000 + 26,000 = 278,000
1949/50 ………… 116,000 + 40,000 + 67,000 + 24,000 = 247,000
1950/51…………..123,000 + 45,000 + 72,000 + 22,000 = 262,000
(c) Vertical scale determination.
Thus; the VS … 1cm represents 50,000 tons.
The graph should be drawn accordingly.
COCOA PURCHASE BY PROVINCE (1947/48 – 1950/51)
Strength of the compound bar graph
It is useful graphical method for showing the cumulative values of more than one cases
Depending on the skill the interpreter has, from the graph, the absolute values are extracted as the value directly shown.
It has perfect replacement by compound line graph
It is comparatively easier to assess the vertical scale to be used.
Setbacks of the compound bar graph
It needs high skill to interpret the graph
It needs high skill to construct the graph
A problem may arise in the selection of the varied textures of the proportional segments
It is very fedious /tiresome as it involve mathematical calculation
It is time consuming in preparation
Percentage bar graph
In percentage bar graph, all bars must be drawn on the same height representing 100% and suitable scale is chosen such as 5, 10, 20 etc, and marked along the sides. The percentages of the total each area stands for must start from zero line. Also it is advised to include the actual percentages of the face of the bars.
Construction of the Percentage bar graph
Consider the given data below showing cocoa purchase by provinces (1947/48 to 1950/51)
| REGION/YEAR | 1947/48 | 1948/49 | 1949/50 | 1950/51 |
| Ashanti | 106,000 | 126,000 | 116,000 | 123,000 |
| W.province | 28,000 | 46,000 | 40,000 | 45,000 |
| E.Province | 54,000 | 80,000 | 67,000 | 72,000 |
| T.Volta | 20,000 | 26,000 | 24,000 | 22,000 |
Procedure
(a) Variables identification
Dependent variable ….. export values
Independent variable … Date (Years).
Y-axis………. purchase values
X-axis………..Years
(b) Cumulative values determination for the dates.
1947/48……….. 106,000 + 28,000 + 54,000 + 20,000 = 208
1948/49………… 126,000 + 46,000 + 80,000 + 26,000 = 278,000
1949/50 ………… 116,000 + 40,000 + 67,000 + 24,000 = 247,000
1950/51…………..123,000 + 45,000 + 72,000 + 22,000 = 262,000
(c) The percentages by provinces in each year determination.
1947/48:
1948/49:
1949/50:
1950/51:
Hence; VS; 1 cm represents 20%
The percentage bar graph should be drawn accordingly as follow:-
COCOA PURCHASE BY PROVINCES (1947/48 – 1950/51)
Vertical scale; 1cm represents 20%
Strengths of the percentage bar graph
It is useful graphical method for showing the values of more than one cases
The data represented appear in a more simplified form as given in percentages.
It is comparatively easier to assess the vertical scale to be used
Setbacks of the percentage bar graph
It does not give the absolute values
It needs high skill to interpret the graph
It needs high skill to construct the graph
A problem may arise in the selection of the varied textures of the proportional segments
It consumes much time to be prepared.
Population pyramid graph
It is a form of bar graph designed to show population distribution by age and sex. It is a double bar chart showing the age sex structure of the population. It consists of two sets of horizontal bars; one is for each sex showing either the p percentages or absolute numbers.
Rules for drawing the population pyramid graph
It is a principle in drawing population pyramid; the number of male population illustrated by the left set of bars; while that of females by the right set of bars.
The young population distribution is always at the bottom while that of old at the top.
Usually the last age group should be left open handled because; some people may survive beyond 100 years and their number have been omitted.
The bottom scale can be graduated as percentages or absolute numbers.
If percentages are opted to be used; the total population of both combined sexes should be used to compute the percentages.
After all the bars have been drawn, they can be shaded in one colour or separated colours for each sex.
CONSTRUCTION OF THE POPULATION PYRAMID
There are two techniques of drawing the horizontal bars of an age sex pyramid. In the first
technique, the bars are drawn proportionally to the actual population numbers (absolute values).
In the second technique, the bars are drawn to represent percentages.
| Age group | Male | Female | Total |
| 0 – 4 | 2291936 | 2242966 | 4534902 |
| 5-9 | 2000580 | 1962556 | 3963136 |
| 10-14 | 2034980 | 2003655 | 4038635 |
| 15-19 | 1681984 | 1721194 | 3403178 |
| 20-24 | 1328529 | 1504389 | 2832918 |
| 25-29 | 1094909 | 11664594 | 2259503 |
| 30-34 | 840692 | 845230 | 1685922 |
| 35-39 | 695263 | 723749 | 1419012 |
| 40-44 | 516502 | 516989 | 1033491 |
| 45-49 | 419841 | 418987 | 838828 |
| 50-54 | 344639 | 340167 | 684806 |
| 55-59 | 223691 | 236325 | 460016 |
| 60-64 | 194513 | 214715 | 409228 |
| 65-69 | 140969 | 160364 | 301333 |
| 70-74 | 118601 | 135524 | 254125 |
| 75-79 | 79166 | 81620 | 160786 |
| 80+ | 95300 | 121038 | 216338 |
| Age not stated | 103487 | 86956 | 190443 |
| All ages | 14205589 | 14481018 | 28686607 |
The absolute value technique
The following steps are followed when constructing a population pyramid using absolute values.
Decide a suitable scale for the horizontal axis (baseline) by considering the values of the biggest and smallest age group, as well as the size of the paper on which the pyramid is to be drawn. Horizontal scale is determined as follows.
Hence by considering the data in the table, scale of 1cm to represent 400,000 people would be suitable.
Choose a suitable scale for the vertical axis. This scale will determine how wide the bars will be and also the interval between the age groups. The width of the bars should not exceed 6mm otherwise the pyramid will look untidy.
Take a clean graph paper and on it draw horizontal axis at least 3 cm from the bottom of the page. Draw two vertical axes of 1 cm apart and about 10 cm long, until they touch the horizontal axis.
Where the vertical axes touch the horizontal axis, mark as zero. On the horizontal axis, and at intervals of 1cm from the zero mark on the both sides, mark of the values representing the female and male population
In the middle column, fill in the age groups starting with the youngest at the bottom. The age groups should be within the width of the horizontal bars.
Using the horizontal scale, and starting with the first age group for females, draw a bar from the vertical axis on the right hand side of the central column towards the right to represent the female population of that group. The scale chosen in step 1 above will determine the length of the bar.
From the left hand side of the vertical axis, draw a bar representing the male population of the same age group. Steps 6 and 7 should be repeated for all the subsequent age group until the last one has been represented.
Fig. 1.1 Kenya: Population by age and sex, 1999
The percentages technique
By this technique, the values for population distribution by age and sex given in percentages. The percentages of each female or male group over the total populations is calculated from the absolute values in our example and a new set of data will be derived from data in the table.
This new data will be used to draw the graph. An example on how to calculate the percentage values is shown below.
The application for calculating the percentage is as follows.
For instance:
The absolute values for the females aged between 0-4 years from the
table is 2242 966, while that for males is 2291936. The total
populations according to the 1999 census, was 28686607. Therefore the
percentage of females is as follows:-
The percentage of male is as follows:-
The worked out percentage values from the figure in the table are given in the table next page.
| Age Group | 5male | %female | Total |
| 1-4 | 8.0 | 7.8 | 15.8 |
| 5-9 | 7.0 | 6.8 | 13.8 |
| 10-14 | 7.1 | 7.0 | 14.1 |
| 15-19 | 5.9 | 6.0 | 11.9 |
| 20-24 | 4.6 | 5.2 | 9.8 |
| 25-29 | 3.8 | 4.1 | 7.9 |
| 30-34 | 2.9 | 2.9 | 5.8 |
| 35-39 | 2.4 | 2.5 | 4.9 |
| 40-44 | 1.8 | 1.8 | 3.6 |
| 45-49 | 1.5 | 1.5 | 3.0 |
| 50-54 | 1.2 | 1.2 | 2.4 |
| 55-59 | 0.8 | 0.8 | 1.6 |
| 60-64 | 0.7 | 0.7 | 1.4 |
| 65-69 | 0.5 | 0.6 | 1.1 |
| 70-74 | 0.4 | 0.5 | 0.9 |
| 75-79 | 0.3 | 0.3 | 0.6 |
| 80+ | 0.3 | 0.4 | 0.7 |
After the calculation of the percentages, the following steps should be taken to come up with the age – sex pyramid.
Choose a suitable scale for the horizontal axis by considering the highest and the lowest percentages in the table. According to the values I the table, a scale of 1cm is representing 1% would be suitable.
Follow step 2 and 3 as outlined under the absolute values techniques discussed earlier.
Where the vertical axis touch the horizontal axis, mark zero and at intervals of 1cm, mark of the percentage value towards the right for females, and towards left for the males.
The age group should be indicated in the middle column just as we did when constructing an age sex pyramid using absolute values..
Using the horizontal scale and starting with age group 0-4 draw a bar on the right hand side to represent the percentage values of the female population in this age group. In our example, the percentage is 7.8 Draw a similar bar on the left hand side to represent the value of the male population, which in our case is 0.8.
Draw bars to represent all the age groups follow steps 9 and 10 under the absolute value technique to complete the pyramid.
Kenya population by age:
Note
Pyramid may also be for the purpose of making comparison either in terms of time or location. This can be by means of a double combined population pyramid. The double combined population pyramid looks as follows.
Advantages of the age-sex pyramid
It is visually attractive method of presenting data.
A variety of information is shown on the same graph. The details include; age, sex and number of people
It can be used to compare the age sex structure of number of countries
It gives a clear picture and summary of the population composition of a country.
Disadvantages of the age-sex pyramid
It is tedious to construct because it involves many values.
It is difficult to tell the exact values represented because of the small scale of the horizontal axis.
Reasons for the differences in population numbers cannot be obtained from the graph directly. Therefore additional information has to be thought from elsewhere.
COMBINED BAR AND LINE GRAPH
It is a form statistical graph designed to have both bars and line to show two attributes whose values appear in varied unit. It is basically employed to show the values of rainfall and temperature together in a year.
In the graph, the bars used to illustrate the values on amount of rainfall in mm or inch, while the line is used to illustrate the values on amount of temperature in C or F. This is also known as climo graph.
Construction of the bar and line graph
Consider the following climatic data for Dar-win weather station Australia.
| Month | J | F | M | A | M | J | J | A | S | O | N | D |
| Temp oC | 28.9 | 27.8 | 28.9 | 29 | 26.7 | 26 | 25.1 | 26.4 | 28.1 | 29.7 | 29.8 | 29 |
| Rain(mm) | 388 | 330 | 246 | 114 | 17.8 | 5 | 2.5 | 2.5 | 12.7 | 53.3 | 132 | 261 |
Procedure
(i) Identification of the variables
· Dependent variable – Rain and temperature values
· Independent variable – Data (months).
Y – -axis – Rain and temperature values
X – axis………..months
(ii) Estimation of the vertical scale to be used
Thus; the vertical scale for rainfall is 1cm to 50mm.
Thus; the vertical scale for temperature is 1 cm to 10 c
(iii) The graph has to be drawn as follows;
CLIMATIC CONDITION FOR DARWIN AUSTRALIA
Strengths of the combined bar and line graph
It is useful graphical method for showing the distribution values of climate
It is more illustrative, as it provides visual idea to the users in statistics.
It allows the easy making of quantitative analysis
Setbacks of the combined bar and line graph
It is more illustrative, as it provides visual idea to the users in statistics
Needs high skill to make quantitative analysis from the graph
It is time consuming graphical method in construction
It needs high skill to construct the graph
It is tedious as it involves mathematical calculation
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