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Related Concept Videos

Population Growth00:57

Population Growth

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Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
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Testing a Claim about Population Proportion01:24

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A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
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Sample Proportion and Population Proportion01:20

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Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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Relative Frequency Histogram01:14

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The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
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Construction of Frequency Distribution01:15

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A frequency distribution table can be constructed using the steps given below.
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Estimating Population Standard Deviation01:26

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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Related Experiment Video

Updated: Mar 24, 2026

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
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Constructing period parity progression ratios from household survey data.

M Murphy, A Berrington

    Studies on Medical and Population Subjects
    |January 1, 1993
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    Summary

    This study uses U.K. Labour Force Survey data to analyze fertility trends. It develops methods to correct biases in period parity progression ratios, offering precise fertility indicators.

    Keywords:
    BiasDemographic FactorsDeveloped CountriesError SourcesEuropeFertilityFertility MeasurementsMeasurementMethodological StudiesNorthern EuropeParityParity Progression RatioPopulationPopulation DynamicsResearch MethodologyUnited Kingdom

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    Area of Science:

    • Demography
    • Sociology
    • Statistics

    Background:

    • Fertility measurement is crucial for demographic analysis.
    • Traditional methods may have limitations in timeliness and precision.
    • Household survey data offers a potential alternative source.

    Purpose of the Study:

    • To apply an own-child analysis to U.K. Labour Force Survey data.
    • To derive period parity progression ratios and total fertility.
    • To assess and correct biases in fertility measures derived from survey data.

    Main Methods:

    • Utilized household composition data from two U.K. Labour Force Survey rounds.
    • Calculated period parity progression ratios and total fertility measure (TFPPR) for up to 20 years.
    • Developed bias correction methods through replication across different survey years.

    Main Results:

    • Identified and quantified biases in fertility measures from survey data.
    • Developed and validated methods for bias correction.
    • Demonstrated the precision and timeliness of corrected fertility indicators.

    Conclusions:

    • U.K. Labour Force Survey data, when adjusted, provides precise and timely period fertility indicators.
    • The developed bias correction methods enhance the reliability of demographic analysis.
    • Own-child analysis offers a valuable tool for routine fertility monitoring.