Null Hypothesis and Hypothesis

¶ … Transient Vibrations and Shock Loads in Spacecraft Components

Increasing performance, as well as the goals of reducing costs, have been the major factors affecting the design of the present and future spacecraft launching system. However, the level of vibration is currently affecting the design process, and launch phase, which may lead to a satellite failure. While it is possible to design the spacecraft to withstand the loads, it is still critical to add a substantial mass to the loads in order to enhance their launching survivability for the satellite operations. However, this option increases the costs of operations as well as reducing the mass margin needed to launch the additional payload. Moreover, on-orbit vibrations can induce spacecraft disturbances leading to negative effects on sensitive payloads' performances. (Denoyer, & Johnson, 2001). Space manipulators have also been identified as the complex systems composing of robotic arms and accommodating the orbiting platform. The space manipulators are effective tools in performing various tasks such as launching satellites, for repairing and maintenance. However, it involves a significant amount of structural vibrations to achieve the launching requirements. Thus, the forces, gravity gradient, orbital perturbations, and second order perturbation can affect the load vibrations. Denoyer, et al. (2001) argue the vibrations of the space aircraft can have an effect on the space missions. Thus, it is very critical to use the "Softride whole-spacecraft vibration isolation system performed very well to reduce structure-borne vibration levels transmitted to the spacecraft." (Denoyer, et al. 2001 p 11). The spacecraft major structural components and dynamic systems can also have an effect on the payloads and the entire systems. The unpredicted changes can have an effect on the launching control systems thereby causing instability and loss of mission. Sabatini et al. (2011) also support the argument by pointing out that loads and vibrations can lead to problems of interaction between the flexible dynamics and control torques in a space manipulator since the dynamic of the space manipulators can be complex. To address the problem, the load analysis has been identified as the effective strategy to establish the load design as well as load testing to evaluate the vibration of the spacecraft.

Statistical Hypothesis

A statistical hypothesis is a process of using the null hypothesis to indicate the tested statistical hypothesis with the purpose of obtaining the motive to reject the null hypothesis. Thus, a statistical hypothesis uses a statistical tool to determine whether a given assumption is true using the null hypothesis.

Difference between Research hypothesis and Statistical Hypothesis

A research hypothesis is defined as a statement of a predicted or expected predicted relationship between two or more variables. A research hypothesis is testable by collecting data on the research interest. In other words, a researcher believes that the truth or falsity of a research can be investigated by collecting data relating to the research interest.

On the other hand, the statistical hypothesis uses the Ho (null hypothesis) and the H1 (alternative hypothesis) to determine no correlation or correlation. The null hypothesis refers to 'no correlation', whereas the alternative hypothesis is denoted as 'a correlation'. Thus, a researcher uses the statistical test to investigate the tenability of the null hypothesis. If the research rejects the null hypothesis, the alternative hypothesis will remain tenable.

Banerjee, et al. (2009) provide the difference between the null hypothesis and alternative hypothesis. The null hypothesis occurs when there are no relationships between the two or more variables under investigation. However, the alternative hypothesis establishes that there is a relationship between two or more variables. Banerjee, et al. (2009) argue that a starting point of a scientific research is to state the hypothesis and a good hypothesis should specific, simple, and be based on the research question. The hypothesis should be stated in advance. The strategy assists in focusing the research objective and create a strong basis for analyzing and interpreting the research findings. Moreover, a simple hypothesis should have one predictor variable as well as one outcome variable, and contain no ambiguity.

Type 1 and Type II Error

The authors also differentiate between type I error and type II error.

"A type I error (false positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type II error (false-negative) occurs if the investigator fails to reject a null hypothesis that is actually false in the population." (Banerjee, et al. 2009 p 3).

Typically, the type I and type II errors can occur if there is a bias in the research procedure. While, it may be difficult to eliminate the type I type II errors entirely, a researcher can reduce their likely to occur if using a large sample size for the research.

P-value

Banerjee, et al. (2009) argue that there is a need to use a statistical test to reject or accept the null hypothesis. The probability (p-values) are very critical in the statistical analysis because it set a parameter to reject or accept the null hypothesis. The statistical significant of 95% is the tool that p-value uses to reject or accept the null hypothesis. For example, if the p-value is less than 5% which is a predetermined level of the research statistical significance, the researcher will reject the null hypothesis in favor of the alternative hypothesis. By setting the significant level at 0.05 or 5%, the researcher will reject the null hypothesis if the significant level of the study is less than 5%.