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1. Explain the concept of random assignment in experimental design and why it is important

Random assignment is the procedure of randomly assigning the participants to an experimental group. It used in the experimental design to create multiple study groups that consist of participants with similar characteristics. Random assignment ensures that the groups under the study are equivalent right from the beginning. The assumption when using random assignment is that the probability of some peculiarity occurring in one group is similar to the probability of it occurring in another group. Random assignment is important helps protect the researcher from the problems of confounding variables and competing explanations. Confounding variables are the correlated predictors that are included in a statistical model that have a significant influence on analysis results.

Since it is impossible to know the relevant variables to include in the experiment, it is important to use random assignment. The use of random assignment creates an even playing field that ensures that groups only differ in their respective assignments. At the end of the research study, a researcher can attribute any changes observed to individual groups by observing and collecting information about individuals at the beginning. This way, random assignment ensures that the researcher has more confidence that any changes that occur do not arise from characteristics of the group but due to the experiment under study.

2. Ways a survey might be designed so as to maximize respondents’ comfort with personal questions.

As a survey researcher, it is critical to provide all answers to the study. However, not all respondents are willing to respond to questions particularly when the questions require the respondent to provide personal or sensitive information. There are various techniques that a researcher might use when designing a survey so as to maximize respondents comfort with personal questions. For example, the researcher might consider conducting an anonymous Survey. With this type of survey, information may not necessarily be linked to a specific person. The respondents can be comfortable enough to provide personal information in this type of survey since their identity remains anonymous.

Secondly, the researcher may consider asking non-Personal Questions First. The researcher can use the technique to build trust with the respondent before progressing through the survey. When the respondents get to know more and about the research, they may feel less imposed by personal questions. Thirdly, the researcher may express Confidentiality by clearly stating the level of confidentiality and security that the respondent information will be. The researcher can do this through an introductory statement that explains how respondents’ feedback will be kept in strict confidence.

Thirdly, the researcher can introduce himself by composing a well-written statement at the beginning of the survey that details the importance of the respondents’ personal information to the survey. The statement can explain the reason for the personal information and how it contributes to the study. The understanding of the necessity of the information increases the chances of getting a positive response. Also, a researcher should limit questions requiring personal information to only those that are more significant to the study. When personal information is not necessary, the researcher should avoid collecting the information.

3. A newspaper reports from a survey that college students study on average seven hours a week for their classes. Identify the statistics and any other information that you would want to know from this survey before making generalizations about the student population at large, and explain why.

There are various statistics and information that may influence the generalization of results from a study. By using the central limit theorem, the sample should be representative of the population from which it is drawn. The greater the desired generalization, the more representative the sample should be. The second information that would be necessary is the types of statistical tests that have been conducted on the results. A statistical test is important in determining the significance level to see the consistency of data with the null hypothesis. It is also necessary to look at the correlation and regression to see the degree of relationship that exists between the variables.

4. What statistics covered in this chapter (Ch. 6 and Ch. 7) would you consider essential for reporting the results of your research project, and why?

Inferential statistics and descriptive statistics are essential when reporting the results of a research project. It is necessary to provide information about our group of data but also necessary to make generalizations about a particular population from which the samples are drawn. From chapter 6, we can see that Descriptive statistics can provide valuable information about the immediate group of data. They give us a lot more in depth data about the sample under the study. However, sampling allows us to only select a representative number from the population. The procedure of a study does not allow us to access the whole population that we are interested in investigating. Unfortunately, it is impossible to go beyond our set of data by using descriptive statistics alone. Inferential statistics is important to help generalize our results to the whole population. This way, we can be able to confirm our hypothesis more easily when using a limited number from the population.

5. Advantages and disadvantages of semantic differential scales in human communication

The semantic differential Measurement scales provide a bipolar adjective for the respondents to choose along a form of scaling. The scale has the capability of examining the strengths and weaknesses of a concept by using the respondent’s ranking. The means of these responses can then be calculated and then plotted or calculated to profile. One advantage of the Semantic Differential question scale is that it allows the semantic differential to measure directionality and intensity. The great number of response can lead to a deeper cognitive processing that in turn should increase response times. It becomes easier to assign numbers to and make a summary statement about their response. It provides a more valid and multi-dimensional method of scaling.