Sampling, Questionnaires, and Instruments - Assignment Example

Chapter Summaries and Case Studies Chapter Summaries Chapter 13 Questionnaires and Instruments Questionnaires refer to a set of structured questions used to collect information from a sample of respondents. They are the most dominant data collection methods and research instruments used by researchers in business and evaluation research (Cooper & Schindler, 2013). We can post, present, or self-administer questionnaires. Measuring quantitative data is the main function of a questionnaire. Respondents complete a sequence of closed-ended questions and open-ended questions in a questionnaire. In most cases, questionnaires entail short closed-ended questions. Business researchers can use questionnaires in the first instance and as the sole research instrument in a business environment since they can collect information from a wider sample. Questionnaires are relatively inexpensive to administer and allow the respondent to complete the questions at their own convenience. However, questionnaires do not offer detailed written responses. In creating effective measurement questions, the research must design tightly aligned and structured questions. They must also consider the order of presenting the questions where the sensitive questions should be at the end of the questionnaire to establish the trust of the respondent. An effective questionnaire should be valid, reliable, and have no double-barreled questions. Chapter 14 Sampling Sampling refers to selecting a specific number of entries from a statistical population to draw further inferences about the entire population. A sample includes relevant demographics that the researchers want to study. Various sampling methods include random sampling, systematic sampling, controlled sampling, quota sampling, and cluster sampling. The type of research determines the sampling method to apply. Random sampling is most effective when analyzing homogeneous sets of data since it involves choosing specific number of entries at random (Cooper & Schindler, 2013). Controlled sampling is most effective in secondary research since it involves takes highly specific entries from a heterogeneous set of data. Quota sampling involves grouping entries into segments with common characteristics while cluster sampling involves grouping entries into geographical groups. In determining the sample size, researchers consider the cost of collecting data and the need for enough statistical power. Moreover, researchers select a manageable sample that can accurately represent the characteristics of the entire population. They also consider the amount of variability in the population, assumptions about the overall population, and the expected margin of error and standard of deviation. In analyzing and presenting the data, researchers rely on sampling. They can adopt the analysis of dependence where the study has one (or more) dependent variables or the analysis of interdependence where there are no dependent variables. The techniques that researchers can use to analyze and present collected data include graphs, tables, the mean, the median, the mode, the range, the interquartile range, the standard deviation, confidence interval, or index numbers. Chapter 15 Data Preparation and Description Data preparation involves editing, coding, and data entry (Cooper & Schindler, 2013). A long process that is prone to many errors. Researchers check the data for accuracy, enter the data into the computer, and transform the data from raw form to reduced and classified forms for exploration. Editing identifies errors and omissions, corrects them when possible, and certifies compliance with maximum data quality standards. Data coding relates to assigning numbers to responses to ensure the study has a limited number of response categories. On the other hand, data entry transforms raw data into classified data and a medium for analysis and manipulation. In case of missing data, the researcher investigates the pattern of missing data to establish the mechanism for the missing data. He then selects an effective missing-data technique to salvage data sets with missing values. List wise deletion, pairwise deletion, and replacement of missing values with estimated scores are effective techniques of handling missing data. In describing data statistically, researchers are able to understand the collected data. Describing data statistically helps in revealing and correcting data entry errors. Chapter 16 Exploring, Displaying, and Examining Data The researcher enhances sense of data displays and is aware that great data exploration and analysis deliver insight from data. Indeed, data quality increases company revenues. Exploratory data analysis techniques provide insights and data diagnostics by emphasizing visual representations of the data. In exploring data, the researcher can respond to the patterns revealed in the preliminary data analysis of the data. Exploring guides the data analysis or suggests revisions to the preliminary data analysis plan. Researchers can use Frequency Table of Ad Recall that arrays category codes from lowest value to highest value and defines the frequency, percent, validity percent, and cumulative percent (Cooper & Schindler, 2013). The researcher can also use a bar chart, pie chart, histogram, Pareto diagrams, and stem-and-leaf display that group data values into intervals and enhances visualization. Cross-tabulation examines relationships involving categorical variables, serves as a framework for later statistical testing, and makes table-based analysis using one or more control variables by comparing data from two or more categorical variables (Cooper & Schindler, 2013). Cross-tabulation is an efficient tool for data visualization and decision-making. Chapter 17 Hypothesis Testing  Hypothesis testing refers to the formal procedures used by statisticians to accept or reject statistical hypotheses (Cooper & Schindler, 2013). Where the sample data are not consistent with the statistical hypothesis, the researcher rejects the hypothesis. Various types of hypothesis include null hypothesis, alternative hypothesis, simple hypothesis, and composite hypothesis. Hypothesis testing procedures adopts six steps that include stating the hypotheses, stating the sample size, stating the test statistic that will conduct the hypothesis test, finding the critical value for the test, calculate the value of the test statistic, and making a decision. Hypothesis testing involves parametric and nonparametric tests. Parametric test relates to a situation where we can know the information about the population by its parameters. A non-parametric test relates to a situation where there is no knowledge about the population or parameters in testing the hypothesis of the population. While non-parametric test are simple and easy to understand, parametric tests are complex and involve assumptions about the parent population. Non-parametric test do not make any assumptions. In hypothesis testing, we have the term “statistically significant difference” that refers to the probability that for a given set of data, the statistical test for a difference between the effects in two groups achieves statistical significance. The amount of information in the data set influences the selection of an appropriate test of statistical significance. Researchers can interpret various test statistics using the Difference-of- means test, analysis of variance, homogeneity of variance, or regression analysis. Chapter 18 Measures of Association Measures of association define the strength of the relationship between two variables (Cooper & Schindler, 2013). When two variables have a perfect relationship with each other, the maximum numerical value is one while the numerical value is zero when there is no relationship between two variables. Researchers can study the relationships between two or more variables through correlation analysis where they consider the effects of a large number of factors on one another through a comparison of conditional probabilities. The measures of association involve the product moment correlation coefficient that measures the degree of scatter or the strength of the correlation between two variables and ranges from – 1to 1. A positive value indicates a positive correlation while a negative value indicates a negative correlation. Regression analysis defines the relationships among variables. Using the method of least squares to minimize errors in drawing a line of best fit, regression analysis can make predictions on the relationships among variables. Spearman’s Rank Order, Phi, Goodman and Kruskals gamma, and Cramer’s V are nonparametric measures of association. They offer the alternative of describing the relationship between two or more sets of observations when the variables are ordinal and not bivariate normal. Chapter 19 Presenting Insights and Findings: Written Reports Research reports present the results of formal inquiry. In writing research reports, researchers must have the knowledge that quality presentation of research findings can have an inordinate effect on an audience’s perceptions of a studys quality (Cooper & Schindler, 2013). A research report includes a title page, table of contents, executive summary, and purpose of the report, background, and research question, review of literature, methodology, results, analysis, conclusion, limitations, recommendations, references, and appendices. A research report should be of considerable length to cover all the details of the study. There are different types of research reports that include journal articles, business reports, presentations at conferences, and theses and dissertations. In writing a research report, the researcher should consider the research question, purpose of the research, limitations, and use of the report. A detailed research report should include visual aids like tables, charts, or graphs to present the data and findings. Chapter 20 Presenting Insights and Findings: Oral Presentations Unlike traditional public speaking, an oral research presentation follows a given pattern and framework, uses a formal language, is short, maximizes the relationship between the presenter and the audience, achieves the presenter’s objectives, addresses a specific audience, and follows specific guidelines and time limits. The historical rhetorical theory has practical influence on business presentation skills in the 21st century because guidelines, language, objectivity, and framework of a business report presentation has not changed (Cooper & Schindler, 2013). In planning for the research presentation, the presenter must address the objectives, audience, venue, and remit. Then he chooses the main points, chooses the supporting information, establishes the linking statements, develops an opening, develops a conclusion, and reviews the presentation. The presentation defines authoritative and relevant materials designed to support the main points. The presentation utilizes effective and good visuals that define the proficiency in research presentations. Getting and holding the audiences attention is important in the oral presentation because it helps in addressing the audience’s needs. To perfect the art of presenting research reports, presenters must do enough practice to enhance their communication skills and objectivity. Case Studies Donatos Finding the New Pizza Donatos adopted a qualitative research design for new product development, Donato’s low-carbohydrate pizza. Indeed, Donatos has a reputation for premium quality and an abundance of toppings in the pizza segment. The research-based product development process entailed the development of a product prototype, followed by employee taste testing, concept screens that involved observations and questionnaires that collected data using short closed-ended questions addressing the item’s uniqueness, brand fit, price attractiveness, and the likelihood of purchase if the product were available (Cooper & Schindler, 2004). The research design also included self-administered intercept survey. Donato used Wassup meetings as an exploratory methodology to help define the research question. These meetings are frequent and effective since they took place on a monthly basis and employees inform the company on the eating habit from popular culture and explain its effect on Donatos with an aim of helping the company to address the effects of changing eating habit on Americans Restaurants (Cooper & Schindler, 2004). This enhances data quality by providing insights and data diagnostics that helps the company to respond to the changing eating habits and other factors that influence restaurants. Donatos used the test market in the research-based product development process. The in-restaurant tests in two or more restaurants within the chain were very effective since it was aware of the research problem and derived informed and relevant response (Cooper & Schindler, 2004). The self-administered intercept survey was convenient for the respondents and encouraged participation. However, the test market was prone to biased response since it involved more restaurants within the chain. Moreover, it eliminated diverse opinion from other chains. For the survey of the in-restaurant product tests, I would have used parametric test measurement scales since there is prior information about the population. Hero Builders This case presents an exploratory study since it depicts a design firm that used exploratory research to define a niche in the action-figure business. HeroBuilders.com conducted prior research to launching its hero and villain action figure business. The research addressed the legal and privacy issues involved in using the likenesses of living heroes like a sitting president for commercial purposes in an effective manner by consulting a lawyer (Cooper & Schindler, 2004). However, the research failed to address the public and media perception that the discovery of the dolls would create. The research studied the industry and market forces by analyzing the competitors in the industry and the position of action figures in the toy store (Cooper & Schindler, 2004). Moreover, the research studied the pricing and marketing segmentation in the industry. Other than those issues that Vicale chose to evaluate, I would have included ethical and cultural issues in my research plan for HeroBuilders.com. Data Development, Inc. Data Development, Inc. is one of the corporations offering data collection and analysis for the purposes of improving market niches for different companies. With a vast array of data collection techniques such as questionnaires, random sampling, calls and emails, the corporation is able to collect useful data for their clients. Interestingly, Data Development, Inc. is able to employ data analysis techniques that translate to useful information for the clients. This way, clients are able to fine-tune their business models, manufacturing processes, marketing and advertising approaches to make a meaningful impact for profitability. As a standalone corporation, they are able to use complicated statistical procedures and provide customers with realistic and predictable market behavior for any given set of research inputs (“Data Development, Inc.,” Case study video). Covering Kids with Health Care ‘Covering Kids with Health Care” case study arguably represents one of the most successful case studies of all times. Wirthlin Worldwide, a business consulting and research firm conducted a comprehensive research on parent’s knowledge about child healthcare program. The U.S government had rolled out a child healthcare program dubbed “State Children’s Health Insurance Program” that little, if any, parents knew about. However, by using integrated research techniques Wirthlin Worldwide was able to identify, among other things, that parents simply did not know anything about it. Following a rigorous research, the company was able to identify the correct marketing strategies to enlighten the public about the healthcare program. One of the key aspects of the integrated research was the ability to identify, through psychological research techniques, the attachment of parents to their children in relation to healthcare. The result of this successful campaign was an enlightened society with large number of parents enrolling their children to the health care program (“Covering Kids with Health Care,” Case study video). References Cooper, D., & Schindler, P. (2004). Donatos: Finding the New Pizza. Retrieved from: file:///C:/Users/Acer/Downloads/DonatosFindingTheNewPizza.pdf Cooper, D., & Schindler, P. (2004). HeroBuilders.com. Retrieved from: file:///C:/Users/Acer/Downloads/HeroBuilders.pdf Cooper, D., & Schindler, P. (2013). Business Research Methods (12th ed). New York, NY: McGraw-Hill Higher Education. Covering Kids with Health Care, video case study, Retrieved from http://bevideos.mhhe.com/business/video_library/0073344974/swf/Clip_03.html Data Development, Inc. video case study, Retrieved from http://bevideos.mhhe.com/business/video_library/0073344974/swf/Clip_05.html Read More