Fundamentals of Testing a Hypothesis
In the statistical field, an inference relating to a property of a sample is referred to as hypothesis while the procedure for assessing the significance of the inference about the property of the sample population is a hypothesis test ( Triola, 2018). Thus, the testing of a hypothesis involves a step-by-step methodological process that permits a person to analyze the variations between the expected results and the observed results of a sample population to determine if the hypothesis is correct. Thus, to test a hypothesis, it is relevant that the null hypothesis is stated by setting two claims that are intended to establish the legitimacy of a statistical statement ( Triola, 2018) . The claims are referred to as the null and alternative hypothesis.
Hypothesis Testing about a Proportion
In this type of testing two procedures can be employed, one is the application of the precise procedure founded on the binomial probability distribution and the second is the application of normal distribution as an estimation to the binomial distribution.
Delegate your assignment to our experts and they will do the rest.
Hypothesis Testing about a Mean
There are two ways in which the hypothesis about a mean can be determined the first being a very realistic approach that is commonly used. This approach consists of the determination of the claim with the standard deviation of the population not being known ( Triola, 2018) . The second approach is the establishment of the hypothesis of a mean with the standard deviation being known. This second approach is rarely used.
Hypothesis Testing about a Variance or Standard Deviation
In the determination of a claim through this procedure involves the application of the chi-square test ( Triola, 2018) . The critical value, P -value, or the confidence interval can be applied as they all arrive at the exact conclusion.
References
Triola, M. F. (2018). Elementary Statistics 13E. Boston, MA: Pearson.
