Testing Statistical Hypotheses - Essay Example

Acceptance of the null hypothesis automatically leads to the rejection of the alternate hypothesis. There is a procedure followed in hypothesis testing. The first step involves stating both the null and alternate hypotheses. The hypothesis is stated in a manner that they are mutually exclusive. The second stage is the determination of the level of significance (Lehmann, 2004). The higher the level of significance, the higher the precision attained. The sample size is then determined to allow for the collection of data.

The size of the data will determine the type of test conducted. After the collection of data, one moves to the stage of data analysis. In this stage, the value of test statistics is calculated e.g. z-value or the t-value (2012). The analysis of the calculated value is made by use of the statistical tables. The table is used to determine if the calculated score falls within the acceptance or rejection region (Lehmann, 2004). The final stage is then made depending on the location of the score. If the calculated value falls in the rejection region, the null hypothesis is rejected implying that there is significant variation in the observation made.

Two kinds of errors can be made in hypothesis testing: type one and type two errors. Type one error is that which leads to the rejection of the null hypothesis which is true whereas type two error is the error of accepting a false null hypothesis. In conclusion, the stages in hypothesis testing if well followed make the hypothesis testing easy to comprehend and make statistical decisions. Hypothesis testing is therefore essential in analyzing data to determine its validity and truthfulness hence important in making statistical decisions.