Chapter 1
The chapter tie into professionalism of specific quality, managerial and research activities in the following ways; firstly, the chapter ties into professionalism since it exposes the key professional subjects through the topic of the engineering experiments. The key aspects of quality, managerial activities and research is to improve the performance of the existing systems, to improve reliability and the product performance. In addition to these, it is also to improve on the time management in the design and in the development of new processes and products and to evaluate materials, design alternatives and to set component and the tolerance of a system. This is in line with the aims of the engineering experiments hence that is how the chapter ties into professionalism, management and research activities. Anything done professionally means that the outcome should be appealing and of a substantial quality. The key pillar of management is planning and so the experimental planning and analysis greatly ties to management.
An example of the bio- mimic technologies of robots that imitate the behavior of animals and use of intelligent systems is a product of the experimental design analysis. This helps to improve quality and the research activities that focuses to make the life of the humans to become easier day by day. All these sill fall under a management system that ensures that everything is in the right place at the required time.
Definition and explanation of the important terms.
Experiment; this term refers to a series of tests mainly used while trying to prove a concept or when one wants to develop something new. This term relates to quality in that the tests carried out through experiments always tries to improve on the state of something and that is quality. This is also part of research since research is mainly about fact finding. The condition if a design also determines the quality of the object in question.
Analysis; this refers to the detailed examination of the structure of something or element and that forms the basis of interpretation or discussion. This is the foundation of research and it ties with management and quality since they are correlating
Design refers to a plan or the drawing of an object form an abstract mind into reality to materialize into workings of an object. Design is also a form of a plan just as management is and any good research must have a good design (Mason et al, 34).
Chapter 2 of Tague: Some Basic Statistical Concepts
Histogram
The histogram is a very useful statistical tool; this is because it shows the distribution of a given set of data. It shows the normal distribution of the data, it can also show the skeweness and the kurtosis of any given data set. Montgomery asserts that from the histogram one can tell whether the data shown follows a normal distribution or not, one can also tell whether the data is skewed to the left or not (Montgomery, 56).
Box plots
The box plots are useful; since they show the difference between two given sets of data, they the difference in the characters of two or more experimental data.
Hypothesis and two sample t-test
Hypothesis testing is of importance because it can tell whether there is statistical significant difference in some given data sets. The two sample t-test aims at comparing the mean of two data sets (Rumsey, 162). The hypothesis of the test can be given as shown below
Ho: U1=U2
H1: U1≠U2
The null hypothesis states that there is no difference in the mean of the two populations while the alternative hypothesis states that there is difference in the mean of the two populations. The procedure is to calculate the test statistic to confirm or reject the null hypothesis. The test statistic is given as
test statistic=y1-y2Sp1n1+1n2
Where y1 is the mean of the first data and y2 is the mean of the second data, n1 and n2 are the frequency of the two populations respectively
SpIs the pooled standard deviation
The test statistic is calculated and the value is cross checked with the t-distribution table. The critical value in the t-distribution table is found by looking at the degree of freedom and the corresponding level of significance. When the t-statistic is between the two given critical values of the t-distribution table then the null hypothesis is not rejected. If the value f the test statistic fall outside the critical value of the t-distribution table then the null hypothesis is rejected.
A second approach that can be used in the two sample t-test is the p-value approach. When the p-value is less than the level of significance then the null hypothesis is rejected. However, if the p-value is greater than the level of significance then the null hypothesis is not rejected.
These statistical approaches are very useful in the research since one can tell whether two samples are statistically similar in the distribution or not. Take for example in comparing the weight two metals, several weighs of the two different metals can be obtained, this two sample t test will be of essence since it can tell whether there is a significant difference in the weight of these two metals.
Work cited
Montgomery, Douglas C. Design and Analysis of Experiments. Hoboken, NJ: Wiley, 2008. Print.
Mason, Robert L, Richard F. Gunst, and James L. Hess. Statistical Design and Analysis of Experiments: With Applications to Engineering and Science. Hoboken, N.J: J. Wiley, 2003. Internet resource.
Rumsey, Deborah J. Intermediate Statistics for Dummies. Hoboken, NJ: Wiley Pub, 2007. Internet resource.
