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Multilingual Demographic Dictionary, second unified edition, English volume

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Multilingual Demographic Dictionary, second unified edition, English vol.
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(Eugene Grebenik et al., first edition 1958)
 
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=== 150 ===
 
=== 150 ===
  
When the movement of a demographic variable in time is considered, a demographic {{TextTerm|time series|1}} is obtained. It is sometimes possible to decompose a time series into a {{TextTerm|trend|2}} around which there are {{TextTerm|fluctuations|3}}, {{TextTerm|variations|3}} ({{RefNumber|14|1|1}}) or {{TextTerm|deviations|3}} ({{RefNumber|14|1|2}}). Where such fluctuations tend to recur after certain periods, they are called {{TextTerm|periodic fluctuations|4}} or sometimes {{TextTerm|cyclical fluctuations|4}}, In demography the most common period is a year, and the fluctuations in sub-periods are called {{TextTerm|seasonal fluctuations|5}}. The fluctuations that remain after trend and periodic fluctuations have been eliminated are called {{TextTerm|irregular fluctuations|6}}. They may be due to exceptional factors, e. g. to mobilization, or sometimes they are {{TextTerm|chance fluctuations|7}} or {{TextTerm|random fluctuations|7}}.
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When values of a demographic variable are available over time, a demographic {{TextTerm|time series|1|150|OtherIndexEntry=series, time ...}} is obtained. It is sometimes possible to decompose a time series into a {{TextTerm|trend|2|150}} around which there are {{TextTerm|fluctuations|3|150|IndexEntry=fluctuation}}, {{TextTerm|variations|3|150|2|IndexEntry=variation}}, or {{TextTerm|deviations|3|150|3|IndexEntry=deviation}} ({{RefNumber|14|1|2}}). Where such fluctuations tend to recur after certain periods, usually several years, they are called {{TextTerm|cyclical fluctuations|4|150|IndexEntry=cyclical fluctuation|OtherIndexEntry=fluctuation, cyclical ...}} or, more generally, {{TextTerm|period fluctuations|4|150|2|IndexEntry=period fluctuation|OtherIndexEntry=fluctuation, period ...}}. In demography the most common period for compiling data is a year, and the fluctuations in sub-periods of a year are called {{TextTerm|seasonal fluctuations|5|150|OtherIndexEntry=fluctuation, seasonal ...}}. The fluctuations that remain after trend, cyclical, and seasonal fluctuations have been eliminated are called {{TextTerm|irregular fluctuations|6|150|IndexEntry=irregular fluctuation|OtherIndexEntry=fluctuation, irregular ...}}. They may be due to exceptional factors such as wartime mobilization, or sometimes they are {{TextTerm|chance fluctuations|7|150|IndexEntry=chance fluctuation|OtherIndexEntry=fluctuation, chance ...}} or {{TextTerm|random fluctuations|7|150|2|IndexEntry=random fluctuation|OtherIndexEntry=fluctuation, random ...}}.
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{{Note|3| In a general sense the term {{NoteTerm|variation}} may be used to describe change in any value or set of values for a variable.}}
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{{Note|4| {{NoteTerm|Periodic|IndexEntry=periodic}}, adj. - {{NoteTerm|period}}, n. - {{NoteTerm|periodicity}}, n. {{NoteTerm|cyclical}}, adj. - {{NoteTerm|cycle}}, n.}}
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{{Note|7| {{NoteTerm|Random|IndexEntry=random}}, adj.: due to chance (cf. {{RefNumber|16|1|1}}).}}
  
 
=== 151 ===
 
=== 151 ===
  
It is occasionally desirable to replace a series of figures by another that shows greater regularity. This process is known as {{TextTerm|graduation|1}} or {{TextTerm|smoothing|1}}, and it generally consists of passing a regular function through a number of points of the time series or other series, such as numbers of persons by reported ages. If a free-hand curve is drawn the process is known as {{TextTerm|graphic graduation|2}}. Where analytical mathematical methods are used, this is called {{TextTerm|curve fitting|3}}. A mathematical curve is fitted to the data, possibly by the {{NoteTerm|method of}} least {{TextTerm|squares|4}}, which minimizes the sum of the squares of the differences between the original and the graduated series. Other methods include {{TextTerm|moving averages|5}} or involve the use of the {{TextTerm|calculus of finite differences|6}}. Some of the procedures may {{NoteTerm|be}} used for {{TextTerm|interpolation|7}}, the estimation of values of the series at points intermediate between given values or for {{TextTerm|extrapolation|8}}, the estimation of values of the series outside the range for which it was given,
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It is occasionally desirable to replace a series of figures by another series that shows greater regularity. This process is known as {{TextTerm|graduation|1|151}} or {{TextTerm|smoothing|1|151|2}}, and it generally consists of passing a smooth curve through a number of points in the time series or other series, such as the number of persons distributed by reported age. If a free-hand curve is drawn the process is called {{TextTerm|graphic graduation|2|151|OtherIndexEntry=graduation, graphic ...}}. When analytical mathematical methods are used, this is called {{TextTerm|curve fitting|3|151|OtherIndexEntry=fitting, curve}}. A mathematical curve is fitted to the data, possibly by the {{TextTerm|method of least squares|4|151|OtherIndexEntry=least squares, method of ...||OtherIndexEntry2=square, method of least squares}}, which minimizes the sum of the squares of the differences between the original and the graduated series. Other methods include {{TextTerm|moving averages|5|151|IndexEntry=moving average|OtherIndexEntry=average, moving ...}} or involve the use of the {{TextTerm|calculus of finite differences|6|151|OtherIndexEntry=difference, calculus of finite differences|OtherIndexEntry2=finite differences, calculus of ...}}. Some of these procedures may be used for {{TextTerm|interpolation|7|151}}, the estimation of values of the series at points intermediate between given values, or for {{TextTerm|extrapolation|8|151}}, the estimation of values outside of the range for which it was given.
{{Note|1| {{NoteTerm|graduation}} n. {{NoteTerm|graduate}} v. {{NoteTerm|graduated}} adj. {{NoteTerm|smoothing}} n. {{NoteTerm|smooth}} v. {{NoteTerm|smoothed}} adj.}}
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{{Note|1| {{NoteTerm|Graduation|IndexEntry=graduation}}, n. - {{NoteTerm|graduate}}, v. - {{NoteTerm|graduated}}, adj. {{NoteTerm|Smoothing}}, n. - {{NoteTerm|smooth}}, v. - {{NoteTerm|smoothed}}, adj.}}
{{Note|7| {{NoteTerm|interpolation}} n. {{NoteTerm|interpolate}} v. {{NoteTerm|interpolated}} adj.}}
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{{Note|7| {{NoteTerm|Interpolation|IndexEntry=interpolation}}, n. - {{NoteTerm|interpolate}}, v. - {{NoteTerm|interpolated}}, adj.}}
{{Note|8| {{NoteTerm|extrapolation}} n. {{NoteTerm|extrapolate}} v. {{NoteTerm|extrapolated}} adj.}}
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{{Note|8| {{NoteTerm|Extrapolation|IndexEntry=extrapolation}}, n. - {{NoteTerm|extrapolate}}, v. - {{NoteTerm|extrapolated}}, adj.}}
  
 
=== 152 ===
 
=== 152 ===
  
It is often necessary to graduate distributions to correct the tendency of people to give their replies in {{TextTerm|round numbers|1}}. This tendency is sometimes referred to as the {{TextTerm|heaping|2}} or {{TextTerm|bunching|2}} of replies at {{TextTerm|preferred points|3}}, {{TextTerm|and indices of heaping|4}} or {{TextTerm|indices of bunching|4}} may be constructed. One {{NoteTerm|of}} the major applications of this method in demography is the adjustment of age distributions, where there is a tendency for people to state their ages in numbers ending with 0, 5 or other preferred digits.
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It is often necessary to graduate distributions to correct the tendency of people to give their replies in {{TextTerm|round numbers|1|152|IndexEntry=round number|OtherIndexEntry=number, round ...}}. {{TextTerm|Heaping|2|152|IndexEntry=heaping}} or {{TextTerm|digit preference|2|152|2|OtherIndexEntry=preference, digit ...}} can be found in various duration distributions (e.g., distribution of marriage duration, breastfeeding duration or birth intervals), but is particularly frequent in age distributions and reflects a tendency for people to state their ages in numbers ending with 0, 5, or other preferred digits, but . {{TextTerm|Age heaping|3|152|IndexEntry=age heaping|OtherIndexEntry=heaping, age ...}} is sometimes measured with {{TextTerm|indices of age preference|4|152|IndexEntry=index of age preference|OtherIndexEntry=age preference, index of ...|OtherIndexEntry2=preference, index of age ...}}. Age data must often be corrected for other forms of {{TextTerm|age misreporting|5|152|OtherIndexEntry=misreporting, age ...}} or {{TextTerm|age reporting bias|5|152|2|OtherIndexEntry=bias, age reporting ...|OtherIndexEntry2=reporting bias, age ...}}
  
 
=== 153 ===
 
=== 153 ===
  
The numerical values of demographic functions are generally listed {{TextTerm|in fables|1}}, such as life tables ({{RefNumber|43|1|1}}), fertility tables ({{RefNumber|63|4|1}}), or nuptiality tables ({{RefNumber|52|2|1}}). A distinction is made between {{TextTerm|current tables|2}} which are based on observations collected during a limited period of time, and {{TextTerm|cohort tables|3}} or {{TextTerm|generation tables|3}}, which deal with the experience of a cohort throughout its lifetime. A similar distinction is made between {{TextTerm|current rates|4}}, which refer to a given period of time, and {{TextTerm|cohort rates|5}} or {{TextTerm|generation rates|5}}, which refer to a cohort.
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The numerical values of demographic functions are generally listed in {{TextTerm|tables|1|153|IndexEntry=table}}, such as {{NonRefTerm|life tables}} ({{RefNumber|43|1|1}}), {{NonRefTerm|fertility tables}} ({{RefNumber|63|4|1}}), or {{NonRefTerm|nuptiality tables}} ({{RefNumber|52|2|1}}). A distinction is usually made between {{TextTerm|calendar-year tables|2|153|IndexEntry=calendar-year table|OtherIndexEntry=table, calendar-year ...|OtherIndexEntry2=year, calendar-... table}} or {{TextTerm|period tables|2|153|2|IndexEntry=period table|OtherIndexEntry=table, period ...}} which are based upon observations collected during a limited period of time, and {{TextTerm|cohort tables|3|153|IndexEntry=cohort table|OtherIndexEntry=table, cohort ...}} or {{TextTerm|generation tables|3|153|2|IndexEntry=generation table|OtherIndexEntry=table, generation ...}} which deal with the experience of a cohort throughout its lifetime. A {{TextTerm|multiple decrement table|4|153|OtherIndexEntry=table, multiple decrement ...|OtherIndexEntry2=decrement, multiple ... table}} illustrates the simultaneous effects of several non-renewable events, such as the effects of first marriage and death on the single population. The most used are {{TextTerm|double decrement tables|4|153|2|IndexEntry=double decrement table|OtherIndexEntry=table, double decrement ...|OtherIndexEntry2=decrement, double ... table}}. {{NewTextTerm|Forecast tables|5|153|IndexEntry=forecast table|OtherIndexEntry=table, forecast ...}} provide numerical values of demographic functions, like {{NonRefTerm|survival functions}} ({{RefNumber|43|1|6}}) for example, which can be used directly for {{NonRefTerm|population forecast}} (cf. {{RefNumber|72|0|2}}). When a population is classified in two or more categories according to age, like economic status (women in the labor force or out of the labor force, for example), marital statuses, regions etc. and when continuous flows between categories are possible over time even if the individual state can usually be measured only at discrete times (waves of a longitudinal study, queries to population registers etc.), {{NewTextTerm|increment-decrement methods|6|153|IndexEntry=increment-decrement method|OtherIndexEntry=method, increment-decrement ...|OtherIndexEntry2=decrement, increment-... method}} or {{NewTextTerm|multi-state methods|6|153|IndexEntry=multi-state method|OtherIndexEntry=method, multi-state ...|OtherIndexEntry2=state, multi-... method}} are more appropriate.
  
 
=== 154 ===
 
=== 154 ===
  
Where insufficient data exist to fix the value of a given variable accurately, attempts may be made to {{TextTerm|estimate|1}} this value. The process is called {{TextTerm|estimation|2}} and the resulting value an {{TextTerm|estimate|3}}. Where data are practically non-existent a {{TextTerm|conjecture|4}} may sometimes be made to fix the variable’s {{TextTerm|order of magnitude|5}}.
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Where insufficient data exist to establish the value of a given variable accurately, attempts may be made to {{TextTerm|estimate|1|154}} this value. The process is called {{TextTerm|estimation|2|154}} and the resulting value an {{TextTerm|estimate|3|154}}. Where data are practically non-existent a {{TextTerm|conjecture|4|154}} may sometimes be made to establish the variable’s {{TextTerm|order of magnitude|5|154|OtherIndexEntry=magnitude, order of ...}} .
  
 
=== 155 ===
 
=== 155 ===
  
Methods of {{TextTerm|graphic representation|1}} or {{TextTerm|diagrammatic representation|1}}
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Methods of {{TextTerm|graphic representation|1|155|OtherIndexEntry=representation, graphic ...}} or {{TextTerm|diagrammatic representation|1|155|2|OtherIndexEntry=representation, diagrammatic ...}} may be used to illustrate the data. The data are represented in a {{TextTerm|figure|2|155}}, {{TextTerm|graph|2|155|2}}, {{TextTerm|statistical chart|3|155|OtherIndexEntry=chart, statistical ...}} or {{TextTerm|map|3|155|2}}. A schematic representation of the relationships between variables is often called a {{TextTerm|diagram|4|155}}, for example the {{NonRefTerm|Lexis Diagram}} (cf. 437). A graph in which one co-ordinate axis is graduated logarithmically and the other arithmetically is called a {{TextTerm|semi-logarithmic graph|5|155|OtherIndexEntry=graph, semi-logarithmic ...|OtherIndexEntry2=logarithmic graph, semi-...}}, though such graphs are often inaccurately referred to as {{TextTerm|logarithmic graphs|5|155|2|IndexEntry=logarithmic graph|OtherIndexEntry=graph, logarithmic ...}}. A {{TextTerm|true logarithmic graph|6|155|OtherIndexEntry=graph, true logarithmic ...|OtherIndexEntry2=logarithmic graph, true ...}} has both axes graduated logarithmically and is sometimes referred to as a {{TextTerm|double logarithmic graph|6|155|2|OtherIndexEntry=logarithmic graph, double ...|OtherIndexEntry2=graph, double logarithmic ...}}. A frequency distribution may be represented graphically by {{TextTerm|frequency polygons|7|155|IndexEntry=frequency polygon|OtherIndexEntry=polygon, frequency ...}} obtained by joining points representing class frequencies with straight lines, by a {{TextTerm|histogram|8|155}}, where class frequencies are represented by the area of a rectangle with the class interval as its base, by {{TextTerm|bar charts|9|155|IndexEntry=bar chart|OtherIndexEntry=chart, bar ...}}, in which the class frequencies are proportionate to the length of a bar or by an {{TextTerm|ogive|10|155}} representing the cumulative frequency distribution.
 
 
<br />may be used to illustrate an argument. Here the data are represented in {{TextTerm|a diagram|2}}, {{TextTerm|graph|2}}, {{TextTerm|figure|2}} (cf. {{RefNumber|13|1|3}}), {{TextTerm|chart|3}} or {{TextTerm|map|3}}. In France the word ''schema'' is used to denote a diagram which gives a {{TextTerm|schematic|4}} representation of a problem. Where in a diagram one co-ordinate axis is graduated logarithmically and the other arithmetically, the graph is called a {{TextTerm|semi-logarithmic graph|5}}, though such graphs are often inaccurately referred to as {{TextTerm|logarithmic graphs|5}}. A true {{TextTerm|logarithmic graph|6}} has both axes graduated logarithmically and is sometimes referred to as a {{TextTerm|double logarithmic graph|6}}. Frequency distribution may be represented graphically by {{TextTerm|frequency polygons|7}}, obtained by joining points representing class frequencies by straight lines, or by {{TextTerm|histograms|8}}, where a class frequency is represented by the area of a rectangle with the class interval as its base, or by {{TextTerm|bar charts|9}}, in which the class frequencies are proportionate to the length of a bar.
 
  
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==<center><font size=12>* * * </font></center>==
 
{{SummaryShort}}
 
{{SummaryShort}}
  
 
{{OtherLanguages|15}}
 
{{OtherLanguages|15}}

Latest revision as of 16:46, 18 July 2017


Disclaimer : The sponsors of Demopaedia do not necessarily agree with all the definitions contained in this version of the Dictionary.

The harmonization of all the second editions of the Multilingual Demographic Dictionary is an ongoing process. Please consult the discussion area of this page for further comments.


Go to: Introduction to Demopædia | Instructions on use | Downloads
Chapters: Preface | 1. General concepts | 2. The treatment and processing of population statistics | 3. Distribution and classification of the population | 4. Mortality and morbidity | 5. Nuptiality | 6. Fertility | 7. Population growth and replacement | 8. Spatial mobility | 9. Economic and social aspects of demography
Pages: 10 | 11 | 12 | 13 | 14 | 15 | 16 | 20 | 21 | 22 | 23 | 30 | 31 | 32 | 33 | 34 | 35 | 40 | 41 | 42 | 43 | 50 | 51 | 52 | 60 | 61 | 62 | 63 | 70 | 71 | 72 | 73 | 80 | 81 | 90 | 91 | 92 | 93
Index: Global Index | Index of chapter 1 | Index of chapter 2 | Index of chapter 3 | Index of chapter 4 | Index of chapter 5 | Index of chapter 6 | Index of chapter 7 | Index of chapter 8 | Index of chapter 9


150

When values of a demographic variable are available over time, a demographic time series 1 is obtained. It is sometimes possible to decompose a time series into a trend 2 around which there are fluctuations 3, variations 3, or deviations 3 (141-2). Where such fluctuations tend to recur after certain periods, usually several years, they are called cyclical fluctuations 4 or, more generally, period fluctuations 4. In demography the most common period for compiling data is a year, and the fluctuations in sub-periods of a year are called seasonal fluctuations 5. The fluctuations that remain after trend, cyclical, and seasonal fluctuations have been eliminated are called irregular fluctuations 6. They may be due to exceptional factors such as wartime mobilization, or sometimes they are chance fluctuations 7 or random fluctuations 7.

  • 3. In a general sense the term variation may be used to describe change in any value or set of values for a variable.
  • 4. Periodic, adj. - period, n. - periodicity, n. cyclical, adj. - cycle, n.
  • 7. Random, adj.: due to chance (cf. 161-1).

151

It is occasionally desirable to replace a series of figures by another series that shows greater regularity. This process is known as graduation 1 or smoothing 1, and it generally consists of passing a smooth curve through a number of points in the time series or other series, such as the number of persons distributed by reported age. If a free-hand curve is drawn the process is called graphic graduation 2. When analytical mathematical methods are used, this is called curve fitting 3. A mathematical curve is fitted to the data, possibly by the method of least squares 4, which minimizes the sum of the squares of the differences between the original and the graduated series. Other methods include moving averages 5 or involve the use of the calculus of finite differences 6. Some of these procedures may be used for interpolation 7, the estimation of values of the series at points intermediate between given values, or for extrapolation 8, the estimation of values outside of the range for which it was given.

  • 1. Graduation, n. - graduate, v. - graduated, adj. Smoothing, n. - smooth, v. - smoothed, adj.
  • 7. Interpolation, n. - interpolate, v. - interpolated, adj.
  • 8. Extrapolation, n. - extrapolate, v. - extrapolated, adj.

152

It is often necessary to graduate distributions to correct the tendency of people to give their replies in round numbers 1. Heaping 2 or digit preference 2 can be found in various duration distributions (e.g., distribution of marriage duration, breastfeeding duration or birth intervals), but is particularly frequent in age distributions and reflects a tendency for people to state their ages in numbers ending with 0, 5, or other preferred digits, but . Age heaping 3 is sometimes measured with indices of age preference 4. Age data must often be corrected for other forms of age misreporting 5 or age reporting bias 5

153

The numerical values of demographic functions are generally listed in tables 1, such as life tables (431-1), fertility tables (634-1), or nuptiality tables (522-1). A distinction is usually made between calendar-year tables 2 or period tables 2 which are based upon observations collected during a limited period of time, and cohort tables 3 or generation tables 3 which deal with the experience of a cohort throughout its lifetime. A multiple decrement table 4 illustrates the simultaneous effects of several non-renewable events, such as the effects of first marriage and death on the single population. The most used are double decrement tables 4. Forecast tables 5★ provide numerical values of demographic functions, like survival functions (431-6) for example, which can be used directly for population forecast (cf. 720-2). When a population is classified in two or more categories according to age, like economic status (women in the labor force or out of the labor force, for example), marital statuses, regions etc. and when continuous flows between categories are possible over time even if the individual state can usually be measured only at discrete times (waves of a longitudinal study, queries to population registers etc.), increment-decrement methods 6★ or multi-state methods 6★ are more appropriate.

154

Where insufficient data exist to establish the value of a given variable accurately, attempts may be made to estimate 1 this value. The process is called estimation 2 and the resulting value an estimate 3. Where data are practically non-existent a conjecture 4 may sometimes be made to establish the variable’s order of magnitude 5 .

155

Methods of graphic representation 1 or diagrammatic representation 1 may be used to illustrate the data. The data are represented in a figure 2, graph 2, statistical chart 3 or map 3. A schematic representation of the relationships between variables is often called a diagram 4, for example the Lexis Diagram (cf. 437). A graph in which one co-ordinate axis is graduated logarithmically and the other arithmetically is called a semi-logarithmic graph 5, though such graphs are often inaccurately referred to as logarithmic graphs 5. A true logarithmic graph 6 has both axes graduated logarithmically and is sometimes referred to as a double logarithmic graph 6. A frequency distribution may be represented graphically by frequency polygons 7 obtained by joining points representing class frequencies with straight lines, by a histogram 8, where class frequencies are represented by the area of a rectangle with the class interval as its base, by bar charts 9, in which the class frequencies are proportionate to the length of a bar or by an ogive 10 representing the cumulative frequency distribution.

* * *

Go to: Introduction to Demopædia | Instructions on use | Downloads
Chapters: Preface | 1. General concepts | 2. The treatment and processing of population statistics | 3. Distribution and classification of the population | 4. Mortality and morbidity | 5. Nuptiality | 6. Fertility | 7. Population growth and replacement | 8. Spatial mobility | 9. Economic and social aspects of demography
Pages: 10 | 11 | 12 | 13 | 14 | 15 | 16 | 20 | 21 | 22 | 23 | 30 | 31 | 32 | 33 | 34 | 35 | 40 | 41 | 42 | 43 | 50 | 51 | 52 | 60 | 61 | 62 | 63 | 70 | 71 | 72 | 73 | 80 | 81 | 90 | 91 | 92 | 93
Index: Global Index | Index of chapter 1 | Index of chapter 2 | Index of chapter 3 | Index of chapter 4 | Index of chapter 5 | Index of chapter 6 | Index of chapter 7 | Index of chapter 8 | Index of chapter 9