Null Hypothesis in the Quantitative Research methods - Assignment Example

Null Hypothesis in the Quantitative Research methods Answers 1. You have been asked to contribute to a brief introduction to the report in which, using simple language, some of the technical aspects of quantitative research methods need to be explained. Your task is to define ‘null hypothesis’ and briefly explain why it is important for understanding inferential statistics. 10 marks - max 100 words A null hypothesis is a statement which expresses a contradiction of what a researcher actually wants to predict, or what the researcher anticipates as the outcome of a scientific inquiry (Ary, Jacobs, Sorensen & Razavieh, 2010). The null hypothesis defines the decision rule, and provides a clearly bound criterion for drawing inferences. Hence, a researcher is able to explain an observed fact associated with data gathered only by properly analyzing the normal curve and accepting or rejecting the null hypothesis. Without a firm grasp of the null hypothesis, hypothesis testing ceases to be the heart of inferential statistics. 2. It is believed that the size of temporary workforces in organisations across the EU is increasing. The EU is interested in whether these increases in temporary workforces vary according to industrial sector. Conduct an analysis to examine the link between SECTOR and TEMPGROWTH; report the findings as fully as you can. 10 marks - max 100 words The chi-square test was used to verify the null hypothesis that “there is no significant association between growth in temporary workforce in EU and the sector which they represent”. The test was performed using two-tailed analysis and a 0.05 level of significance. Results showed that there is no significant link between the increases in temporary workforces in the EU and the industrial sector where these workforces are employed [χ2 (2, N = 218) = 1.124, p = .570)]. There were, however, 28 or 12.8% of data missing, which resulted to only 190 or 87.2% valid data. 3. Answer one of the following two questions (either 3a or 3b): a. In order to better evaluate whether the sizes of temporary workforces are increasing, the EU is interested in the detailed evidence produced by the research regarding recent fluctuations. Examine the data to see if the organisations’ temporary workforces differ between 2009 and 2010. Compare these figures to the anticipated size of temporary workforces in 2011. What does the data indicate? 15 marks - max 200 words The following null hypotheses were tested using two-tailed analysis, 0.05 level of significance and paired samples t-test: (1) there is no significant difference in the size of temporary workforce in 2009 and 2010; (2) there is no significance difference in the size of temporary workforce in 2009 and the anticipated workforce in 2011; and (3) there is no significance difference in the size of temporary workforce in 2009 and the anticipated workforce in 2011. In hypothesis (1), the t-test was significant: t(217)=9.744, p= Read More