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Population proportion

About: Population proportion is a research topic. Over the lifetime, 247 publications have been published within this topic receiving 4099 citations.


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Journal ArticleDOI
01 Dec 2018
TL;DR: The authors derived a bound for the variance of unbiased estimator of the finite population proportion under inverse sampling without replacement, and showed that this bound holds for any estimator under the assumption that the population proportion is finite.
Abstract: In this paper we derive a bound for the variance of unbiased estimator of the finite population proportion under inverse sampling without replacement.

1 citations

Posted ContentDOI
TL;DR: In this article, the authors proposed estimators based on geometric and harmonic mean for estimating population mean using information on two auxiliary attributes in simple random sampling, and they showed that when they have multi-auxiliary attributes, estimators are less biased than Olkin (1958), Naik and Gupta (1996) and Singh (1967) type- estimator under certain conditions.
Abstract: In the present study, we propose estimators based on geometric and harmonic mean for estimating population mean using information on two auxiliary attributes in simple random sampling. We have shown that, when we have multi-auxiliary attributes, estimators based on geometric mean and harmonic mean are less biased than Olkin (1958), Naik and Gupta (1996) and Singh (1967) type- estimator under certain conditions. However, the MSE of Olkin(1958) estimator and geometric and harmonic estimators are same up to the first order of approximation.

1 citations

Book ChapterDOI
01 Jan 2013
TL;DR: This chapter discusses statistical inference, which deals with drawing conclusions about an entire population based on data in a sample drawn from that population through estimation, hypothesis testing, and prediction.
Abstract: Statistical inference is drawing conclusions about an entire population based on data in a sample drawn from that population. From both frequentist and Bayesian perspectives, there are three main goals of inference: estimation, hypothesis testing, and prediction. Estimation and hypothesis testing deal with drawing conclusions about unknown and unobservable population parameters.

1 citations

BookDOI
16 Mar 2010
TL;DR: In this paper, a two-tailed test for the population proportion and a one-tailed alternative for the proportion of the population to the population mean were used to test whether a given set of variables in a time series represents a relationship between a single variable and another variable.
Abstract: Introduction to Statistics What Is Statistics Good for? Some Further Applications of Statistics Some Basic Statistical Ideas On Studying Statistics Describing Data: Tables and Graphs Looking at a Single Variable Looking for Relationships Looking at Variables over Time Describing Data: Summary Statistics When Pictures Will Not Do Measures of a Single Numeric Variable Measures of a Single Categorical Variable Measures of a Relationship Basic Probability Why Probability? The Basics Computing Probabilities Some Tools That May Help Revising Probabilities with Bayes' Theorem Probability Distributions Discrete Random Variables The Binomial Probability Distribution Continuous Random Variables The Normal Distribution: The Bell-Shaped Curve The Normal Approximation to the Binomial Sampling and Sampling Distributions Sampling What Are Sampling Distributions and Why Are They Interesting? The Sampling Distribution of a Proportion The Sampling Distribution of a Mean: sigmaX Known The Sampling Distribution of a Mean: sigmaX Unknown Other Sampling Distributions Estimation and Confidence Intervals Point and Interval Estimators of Unknown Population Parameters Estimates of the Population Proportion Estimates of the Population Mean A Final Word on Confidence Intervals Tests of Hypotheses: One-Sample Tests Testing a Claim: Type I and Type II Errors A Two-Tailed Test for the Population Proportion A One-Tailed Alternative for the Population Proportion Tests for the Population Mean A Two-Tailed Test for the Population Mean A One-Tailed Alternative for the Population Mean A Final Word on One-Sample Tests Tests of Hypotheses: Two-Sample Tests Looking for Relationships Again A Difference in Population Proportions A Difference in Population Means A Difference in Means: sigmas Known A Difference in Means: sigmas Unknown but Equal A Difference in Means: sigmas Unknown and Unequal A Difference in Means: Using Paired Data A Final Word on Two-Sample Tests Tests of Hypotheses: Contingency and Goodness-of-Fit A Difference in Proportions: An Alternate Approach Contingency Tables with Several Rows and/or Columns A Final Word on Contingency Tables Testing for Goodness-of-Fit A Final Example on Testing for Goodness-of-Fit Tests of Hypotheses: ANOVA and Tests of Variances A Difference in Means: An Alternate Approach ANOVA with Several Categories A Final Word on ANOVA A Difference in Population Variances Simple Regression and Correlation The Population Regression Line The Sample Regression Line Evaluating the Sample Regression Line Evaluating the Sample Regression Slope The Relationship of F and t: Here and Beyond Predictions Using the Regression Line Regression and Correlation Another Example Dummy Explanatory Variables The Need for Multiple Regression Multiple Regression Extensions of Regression Analysis The Population Regression Line The Sample Regression Line Evaluating the Sample Regression Line Evaluating the Sample Regression Slopes Predictions Using the Regression Line Categorical Variables Estimating Curved Lines Additional Examples Time-Series Analysis Exploiting Patterns over Time The Basic Components of a Time Series Moving Averages Seasonal Variation The Long-Term Trend The Business Cycle Putting It All Together: Forecasting Another Example Appendix A Appendix B: Answers to Odd-Numbered Exercises Appendix C Index

1 citations

01 Jan 2013

1 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202112
202017
201914
201813
201713
201613