Sample Size is the number of observations or data points or objects in a sample. Sufficiency of sample size is a key element in hypothesis testing to be able to make inferences about the population. The right sample size is primarily dependent on the cost & time involved in data collection and the need for statistical significance. Statistically, sample size is affected by the following parameters
a. Significance Level (σ) or the maximum allowed probability of committing Type I error
b. Power of the test (1-β), where β is the maximum allowed probability of committing Type II error
c. Minimum difference (in the test statistic) to be detected
Regression Analysis is a statistical tool that defines the relationship between two continuous variables. It uses data on relevant variables to develop a prediction equation, or model. It generates an equation to describe the statistical relationship between one or more predictors and the response variable and to predict new observations
An application-oriented question on the topic along with responses can be seen below. The best answer was provided by
Natwar Lal on 21st June 2019.
Applause for all the respondents- Natwar Lal, Sandra Thomas, Chris Marince, Kevin Naya, Sridhar Narayanam.
Also review the answer provided by Mr Venugopal R, Benchmark Six Sigma's in-house expert.