Professional Research And Communication For Research Design And Methodology

Importance of Sample Size in Online Survey

Discuss about the Professional Research and Communication for Research Design and Methodology.

1. The table below shows the responses regarding perception of 100 customers towards the quality of food supplied by the retail food store. In this case, the score is obtained by multiplying the 

Rating on Likert Scale	Number of Responses	Responses Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper
1. Strongly Disagree	14	14
2. Disagree	16	32
3. Unsure	26	52
4. Agree	14	28
5. Strongly Agree	30	15
Total	100	141
		141/100=1.41

total number of respondents provided by the respondents with the assigned rating number of the Likert scale. This process of multiplying the number of responses to the rating is erroneous as it fails to represent the proportion of the respondents in favor of the statements.

 A better measure for evaluation of the perception of the customers towards the quality of the food products of the company can be central tendency (Weiss and Weiss 2012). The calculation of the mean of the responses of the customers can be calculated by adding up all the numbers and then dividing by the total number of responses. The can help in arriving at a certain middle value. Again, the median represents the appropriate middle value (Gentle et al. 2012). The median can be enumerated by list listing the figures in a numerical figure. The mode represents the data that occurs most frequently. The mean as a measure of the central tendency can be considered as a better dimension as it can appropriately summarize the data into a single index number (Andersen et al. 2012). This can represent the entre data as a whole. In addition to this, the central tendency can also help in comparison of the data that can identify the most appropriate single value that is representative of the entire frequency distribution (Weiss and Weiss 2012) Again, the mean can also provide an accurate description of the data (MacDonald 2012).

2. Yes, the results of the study can alter if the selected and the reprehensive sample of the study do not participate in the survey. The non-participation of the lower number of people in the online survey can lead to errors as the small, number of samples might not adequately represent the entire target population of the study. The chances of failing to include an unsatisfied customer are more or less 35%. Therefore, the participation of smaller number of samples can overlook many targeted population. In addition to this, the participation of lower number of respondents can also lead to biased results that can overlook the viewpoints of many participants.

In addition to this, the variability that is determined by essentially the standard deviation of the selected sample are derived from the samples of the study. Therefore, the smaller size of the sample due to the non-participation of the respondents can lead to movements of the samples from the population. Furthermore, this can also affect the overall dependability of the project as this non-participation of the respondents can lead to smaller size of the samples and higher variability. This in turn can lead to biases that can occur due to lack of response. 

3. The data on the gender of the respondents are regarded as the nominal value or else observations that can assign a definite code in the form of a specific number and the numbers can be considered to be simply labels. One can count the nominal values but not place the data in order or else measure the overall nominal data (Berenson et al. 2012).

• The values in the Fahrenheit Thermometers that reflects the temperatures in Fahrenheit are essentially interval variables. The temperature enumerated in Fahrenheit can be regarded as the variables that can be enumerated in a continuum and can have different numerical value (Berenson et al. 2012).
• The Kelvin thermometers that collect values representing temperatures in Kelvin can be regarded as the ratio variables. The temperature measured in Kelvin is essentially a ratio variable as zero Kelvin reflects the fact that there is no temperature whatsoever (Andersen et al. 2012).
• The number of items a customer purchases in whole numbers can be regarded as the
• Bank account balance can be regarded as an interval as the people might have both zero balance or else negative balance in their account (Weiss and Weiss 2012).

Understanding Nominal Value

4. Non-experimental research can be regarded as the research that is short of the handling of an independent variable and random assignment of different participants to diverse conditions or else orders of circumstances or both (Gentle et al. 2012). Experimental study can be conducted for examination of the effect of drinking orange juice on the performance of the players in the weekend. The learner can carry out the non-experimental quantitative research by making use of numerical or else he quantifiable data. The results of the experiment are mainly based on objectives as well as systematic observations (Pickard 2012). The variables of the research that includes performance of the players and many others can be identified that are quantifiable. However, the non-experimental studies can be descriptive, predictive, and explanatory (Marczyk et al. 2010). The descriptive study can track the changes in the behaviors and attitudes of the players and set different indicators for identification of responses of the participants towards a particular stimuli. The explanatory theory is essentially based on the attachment concept that offers a feeling of safety and can examine the associations between variables of attachments (Gall et al. 2010).

Quasi-experimental studies are essentially the subjects to concerns concerning internal validity for that reason the treatment and control groups might not be comparable at the baseline (John Kuada 2012). In the case of random experiments, the participants of the study have equal opportunity of getting selected to a particular intervention group or else the comparison group. The quasi experimental design can be referred to as the process that takes into consideration three different designs that include uncontrolled before as well as after studies, diverse time series design and controlled before and after studies (Marczyk et al. 2010). Here, quasi experiments can also be carried out for testing the impact of drinking juices on the performances of the players in the weekend. Here, the uncontrolled studies both before and after specific intervention can be checked and the variances due to the interventions can also be evaluated to evaluate the effects of the drinking juices on performance of players. This is a simple study although is better than just the observational study. The sudden alterations in the trends can make it challenging as the observed alteration might possibly due to the alterations. The quasi experiments can also make use of the time series designs that recognize different interventions and affect the entire trend. A time series analysis can also be carried out for calculating the performance against time. Controlled before and after studies can be carried out where data can be gathered out both before and after interventions (MacDonald 2012).

Non-Experimental Research

An experiment is essentially a study that incorporates a treatment, a method and a program that is intentionally introduced and an outcome can be observed (Mackey and Gass 2015). In case if an experimental study is conducted, then four essential elements need to be incorporated in the system. The process of the experimental study essentially includes the procedures of manipulation, control, process of random assignment as well as random selection. The researcher can change the circumstances as per the requirements of the study and manipulate the entire environment. Again, the experimental study can be both manipulated and controlled for the purpose of arriving at the outcomes (Graziano and Raulin 2010). Furthermore, experiments refer to the procedures that involve the efforts to minimize different errors as well as biases that can increase the confidence that in turn can manipulate the outcome. Moreover, the experimental study can also include the process of random assignments. A procedure is also employed to evaluate impacts of different alterations and treatment is essentially to make different measurements both before as well as after then treatment and carry out a comparative study after the assignment. In order to arrive at the conclusive results, statistical analysis can be out for the purpose of obtaining conclusive outcomes. The hypotheses testing procedure can be carried out where he null hypothesis can be stated as “There is no difference between the player’s drinking the juices on their performance”. The alternative hypothesis in this regard can be “there exists a variance between the pre and post the situation of drinking juices on performance of the players. A paired t test can be carried out for testing the hypothesis. Here, two different paired variables expressed as the paired variable where the selection of the first variable primarily followed by the pre variable can be carried out. Again, the paired sample statistics can provide the mean, standard deviation, numbers and standard errors for both before and after treatment (Leary 2011). The p value in the paired sample test can help in arriving at the results.

References

Andersen, P.K., Borgan, O., Gill, R.D. and Keiding, N., 2012. Statistical models based on counting processes. Springer Science & Business Media.

Berenson, M., Levine, D., Szabat, K.A. and Krehbiel, T.C., 2012. Basic business statistics: Concepts and applications. Pearson Higher Education AU.

Gall, M.D., Borg, W.R. and Gall, J.P., 2010. Educational research: An introduction . Longman Publishing.

Gentle, J.E., Härdle, W.K. and Mori, Y. eds., 2012. Handbook of computational statistics: concepts and methods. Springer Science & Business Media.

Graziano, A.M. and Raulin, M.L., .2010 Research methods: A process of inquiry . HarperCollins College Publishers.

John Kuada, 2012. Research methodology: A project guide for university students. Samfundslitteratur.

Leary, M.R., 2011. Introduction to behavioral research methods. Pearson Higher Ed.

MacDonald, C., 2012. Understanding participatory action research: A qualitative research methodology option. The Canadian Journal of Action Research, 13(2), pp.34-50.

Mackey, A. and Gass, S.M., 2015. Second language research: Methodology and design. Routledge.

Marczyk, G., DeMatteo, D. and Festinger, D., 2010. Essentials of research design and methodology. John Wiley & Sons Inc.

Pickard, A., 2012. Research methods in information. Facet publishing.

Weiss, N.A. and Weiss, C.A., 2012. Introductory statistics. London: Pearson Education.