Abstract
Statistical inference is to infer whether or not the observed sample data are evidencing the population characteristics of interest. If the whole population data were gathered collectively then there is no room for uncertainty about the population due to a sampling and the statistical inference is unnecessary. It is ideal but unrealistic to collect the whole population data and complete the investigation solely by descriptive data analysis. For this reason, a smaller size of sample data set than that of the whole population is gathered for an investigation. Since the sample data set does not populate the entire population, it is not identical to the population. This chapter will discuss the relationship between the population and sample by addressing (1) the uncertainty and errors in the sample, (2) underpinnings that are necessary for a sound understanding of the applied methods of statistical inference, (3) forms and paradigms of drawing inference, and (4) good study design as a solution to minimize the unavoidable errors contained in the sampling.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Beaumont GP (1980) Intermediate mathematical statistics. Chapman & Hall, London
Cochran WG (1963) Sampling Techniques (2nd Edition). Wiley, NY
Gosset WS (1908) The probable error of a mean. Biometrika 6(1):1–25
Hoel PG (1984) Introduction to mathematical statistics, 5th edn. Wiley, New York
Hogg RV, Tanis EA (2010) Probability and statistical inference, 8th edn. Prentice Hall, New Jersey
Johnson NL, Kotz S, Balakrishnan N (1994a) Continuous univariate distributions, vol 1, 2nd edn. Wiley, New York
Johnson NL, Kotz S, Balakrishnan N (1994b) Continuous univariate distributions, vol 2, 2nd edn. Wiley, New York
Lindgren B (1993) Statistical theory, 4th edn. Chapman & Hall, London
Mood AM, Graybill FA, Boes DC (1974) Introduction to the theory of statistics, 3rd edn. McGraw-Hill, New York
Morton RF, Hebel JR, McCarter RJ (1996) A study guide to epidemiology and biostatistics, 4th edn. Aspen Publishers, Rockville
Pagano M, Gauvreau K (1993) Principles of biostatistics. Duxbury Press, Belmont
Snecdecor GW, Cochran WG (1991) Statistical methods, 8th edn. Oxford, Wiley–Blackwell
Williams B (1978) A sampler on sampling. Wiley, New York
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Lee, H. (2014). Statistical Inference Focusing on a Single Mean. In: Foundations of Applied Statistical Methods. Springer, Cham. https://doi.org/10.1007/978-3-319-02402-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-02402-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02401-1
Online ISBN: 978-3-319-02402-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)