Sampling distributions & estimation of parameters

Sampling distributions & estimation of parameters

Chapter 17, Inferential Statistics

Polit, D. F., & Beck, C. T. (2012). Nursing research: Generating and assessing evidence for nursing practice (Laureate Education, Inc., custom ed.). Philadelphia, PA: Lippincott Williams & Wilkins.

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Sampling distributions & estimation of parameters

Study sheet

What is statistics  It refers to a numerical measurement describing some  In nursing, researchers are a therefore required to understand how to use these statistics to carry out their various analysis. Understanding various situations and phenomenon is very critical and part of their duties hence needs to understand how to use them. Sampling distribution and estimation of parameters is therefore essential for the nurses that conduct researches (Polit & Beck, 2012).   Definition of a parameter  It refers to a numerical measurements describing some characteristics of a population (Polit & Beck, 2012).
 Example of statistics sample mean ( _X ) sample proportion ( ^p ) sample variance ( s2) sample std deviation (s)   Examples  of parameters pop. mean (µ) pop. proportion (p ) pop. variance (δ2) pop. std deviation (δ)  
Characteristics of a sample Sampling distribution sampling distribution is also  known as finite-sample distribution  It is probability distribution of a certain statistics  that is based on random sample         Methods of estimating parameters  There are various methods that   researchers’ use to estimate the parameters.  In estimating parameters researchers are required to know the sampling theory and the statistical inferences  Methods include Least squares methods presented under the forms of simple linear regression, multiple linear model, and non-linear models.  These are also categorized  or known as method of Gauss-Newton. Least square method use iterative processes requiring adoption of initial values.  
Their importance They help  to simplify the routes to statistics inference Allow analytical considerations to be based on the sampling distribution of a given statistics as opposed to joint probability distribution of the entire individual sample values (Polit & Beck, 2012). 
Calculation of  sampling distribution  The key points/ideas to note include: One is require to obtain all the random sample of size from the population of study Then determine the value of the statistic for every sample Lastly, is to obtain the expected value and variability of the statistics.   
 Example Distribution sample mean Consider the Population (1, 2, 3), N = 3 population mean = 2, and pop. variance = 2/3 
Conclusion Researchers should have skills on how to use these statistical methods to s enhance their studies. 
  

Reference

Polit, D. F., & Beck, C. T. (2012). Nursing research: Generating and assessing evidence for        nursing practice (Laureate Education, Inc., custom ed.). Philadelphia, PA: Lippincott         Williams & Wilkins.

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