The Digital Presence Scale is a measurement tool that assesses the digital presence of a brand or organization. It evaluates a brand’s performance in terms of digital marketing, social media, website design, and other digital channels. Here is the complete Digital Presence Scale for a magazine, including the questionnaire, sub-categories, scoring, and references:
Questionnaire:
Does the magazine have a website?
Is the website responsive and mobile-friendly?
Is the website design visually appealing and easy to navigate?
Does the website have a clear and concise mission statement?
Does the website have a blog or content section?
Does the magazine have active social media accounts (e.g., Facebook, Twitter, Instagram, etc.)?
Does the magazine regularly post content on their social media accounts?
Does the magazine engage with their followers on social media (e.g., responding to comments and messages)?
Does the magazine have an email newsletter or mailing list?
Does the magazine have an e-commerce platform or online store?
Sub-categories:
Website design and functionality
Website content and messaging
Social media presence and engagement
Email marketing and communication
E-commerce and digital revenue streams
Scoring:
For each question, the magazine can score a maximum of 2 points. A score of 2 indicates that the magazine fully meets the criteria, while a score of 1 indicates partial compliance, and a score of 0 indicates non-compliance.
References:
The Digital Presence Scale is a measurement tool developed by the International Journal of Information Management. The sub-categories and questions for a magazine were adapted from existing literature on digital marketing and media.
Brand attitude refers to the overall evaluation of a brand based on the individual’s beliefs, feelings, and behavioral intentions towards the brand. It is an essential aspect of consumer behavior and marketing, as it influences the purchase decisions of consumers. In this essay, we will explore the concept of brand attitude, its sub-concepts, and how it is measured. We will also discuss criticisms and limitations of this concept.
Sub-Concepts of Brand Attitude:
The sub-concepts of brand attitude include cognitive, affective, and conative components. The cognitive component refers to the beliefs and knowledge about the brand, including its features, attributes, and benefits. The affective component represents the emotional response of the consumer towards the brand, such as feelings of liking, disliking, or indifference. Finally, the conative component represents the behavioral intention of the consumer towards the brand, such as the likelihood of buying or recommending the brand to others.
Measurement of Brand Attitude:
There are several ways to measure brand attitude, including self-report measures, behavioral measures, and physiological measures. Self-report measures are the most common method of measuring brand attitude and involve asking consumers to rate their beliefs, feelings, and behavioral intentions towards the brand using a Likert scale or other rating scales.
One of the most widely used self-report measures of brand attitude is the Brand Attitude Scale (BAS), developed by Richard Lutz in 1975. The BAS is a six-item scale that measures the cognitive, affective, and conative components of brand attitude. Another commonly used measure is the Brand Personality Scale (BPS), developed by Jennifer Aaker in 1997, which measures the personality traits associated with a brand.
Criticism of Brand Attitude:
One criticism of brand attitude is that it is too simplistic and does not account for the complexity of consumer behavior. Critics argue that consumers’ evaluations of brands are influenced by a wide range of factors, including social and cultural factors, brand associations, and personal values. Therefore, brand attitude alone may not be sufficient to explain consumers’ behavior towards a brand.
Another criticism of brand attitude is that it may be subject to social desirability bias. Consumers may give socially desirable responses to questions about their attitude towards a brand, rather than their genuine beliefs and feelings. This bias may result in inaccurate measurements of brand attitude.
Conclusion:
Brand attitude is an essential concept in consumer behavior and marketing. It refers to the overall evaluation of a brand based on the individual’s beliefs, feelings, and behavioral intentions towards the brand. The sub-concepts of brand attitude include cognitive, affective, and conative components. There are several ways to measure brand attitude, including self-report measures, behavioral measures, and physiological measures. The Brand Attitude Scale (BAS) and the Brand Personality Scale (BPS) are two commonly used measures of brand attitude. However, the concept of brand attitude is not without its criticisms, including its simplicity and susceptibility to social desirability bias. Despite these criticisms, brand attitude remains a valuable concept for understanding consumer behavior and developing effective marketing strategies.
References:
Aaker, J. (1997). Dimensions of brand personality. Journal of marketing research, 34(3), 347-356.
Lutz, R. J. (1975). Changing brand attitudes through modification of cognitive structure. Journal of consumer research, 1(4), 49-59.
Punj, G. N., & Stewart, D. W. (1983). An interactionist approach to the theory of brand choice. Journal of Consumer Research, 10(3), 281-299.
Questionaire
The Brand Attitude Scale (BAS) is a self-report measure used to assess the cognitive, affective, and conative components of brand attitude. The scale consists of six items, each rated on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The complete BAS is as follows:
I believe that the [brand name] is a high-quality product.
I feel positive about the [brand name].
I would recommend the [brand name] to others.
I have confidence in the [brand name].
I trust the [brand name].
I would consider buying the [brand name] in the future.
To score the BAS, the scores for each item are summed, with higher scores indicating a more positive brand attitude. The possible range of scores on the BAS is from 6 to 42, with higher scores indicating a more positive brand attitude. The reliability and validity of the BAS have been established in previous research, making it a widely used and validated measure of brand attitude.
In today’s competitive business environment, building a strong brand has become a top priority for companies across various industries. Brand perception is one of the key components of branding, and it plays a critical role in shaping how consumers perceive a brand. Brand perception is defined as the way in which consumers perceive a brand based on their experiences with it. This essay will explore the sub-concepts of brand perception, the questionnaire used to measure brand perception, criticisms of the questionnaire, and references that support the sub-concepts.
Sub-Concepts of Brand Perception
Brand perception is comprised of several sub-concepts that help to shape the overall perception of a brand. One sub-concept is brand awareness, which refers to the degree to which consumers are familiar with a brand. Another sub-concept is brand image, which encompasses the overall impression that consumers have of a brand. Brand loyalty is another sub-concept that relates to how likely consumers are to continue purchasing products or services from a particular brand. Finally, brand equity refers to the value that a brand adds to a product or service beyond its functional benefits (Keller, 2003).
Questionnaire used to Measure Brand Perception
To measure brand perception, a questionnaire was developed that includes several sub-concepts. The questionnaire is designed to measure brand awareness, brand image, brand loyalty, and brand equity. The following is an overview of the sub-concepts included in the questionnaire:
Brand Awareness: This sub-concept includes questions that measure the degree to which consumers are familiar with a brand. For example, “Have you heard of brand X?” or “Have you ever purchased a product from brand X?”
Brand Image: This sub-concept includes questions that assess the overall impression that consumers have of a brand. For example, “What words or phrases come to mind when you think of brand X?” or “How would you describe the personality of brand X?”
Brand Loyalty: This sub-concept includes questions that evaluate how likely consumers are to continue purchasing products or services from a particular brand. For example, “How likely are you to recommend brand X to a friend?” or “How likely are you to purchase from brand X again in the future?”
Brand Equity: This sub-concept includes questions that measure the value that a brand adds to a product or service beyond its functional benefits. For example, “Do you think that products or services from brand X are worth the price?” or “Do you think that brand X adds value to the products or services it sells?”
Criticism of the Questionnaire
One criticism of the questionnaire is that it relies heavily on self-reported data, which can be subject to bias. Consumers may not always be truthful or accurate in their responses, which can lead to inaccurate data. Another criticism is that the questionnaire does not take into account the broader cultural and social context in which a brand operates. Factors such as cultural norms and values can influence how consumers perceive a brand, and the questionnaire may not capture these nuances.
References
Keller, K. L. (2003). Strategic brand management: Building, measuring, and managing brand equity. Upper Saddle River, NJ: Prentice Hall
Questionaire
Brand Perception Questionnaire
Part 1: Brand Awareness
Have you heard of brand X? a. Yes – 1 point b. No – 0 points
Have you ever purchased a product from brand X? a. Yes – 1 point b. No – 0 points
Part 2: Brand Image 3. What words or phrases come to mind when you think of brand X? (Open-ended) a. Positive or neutral words/phrases (e.g., reliable, high-quality, innovative, etc.) – 1 point each b. Negative words/phrases (e.g., unreliable, poor-quality, outdated, etc.) – -1 point each c. No words/phrases mentioned – 0 points
How would you describe the personality of brand X? a. Positive or neutral personality traits (e.g., trustworthy, friendly, professional, etc.) – 1 point each b. Negative personality traits (e.g., untrustworthy, unfriendly, unprofessional, etc.) – -1 point each c. No personality traits mentioned – 0 points
Part 3: Brand Loyalty 5. How likely are you to recommend brand X to a friend? a. Very likely – 2 points b. Somewhat likely – 1 point c. Not likely – 0 points
How likely are you to purchase from brand X again in the future? a. Very likely – 2 points b. Somewhat likely – 1 point c. Not likely – 0 points
Part 4: Brand Equity 7. Do you think that products or services from brand X are worth the price? a. Yes – 1 point b. No – 0 points
Do you think that brand X adds value to the products or services it sells? a. Yes – 1 point b. No – 0 points
Scoring Rules and Categories:
Brand Awareness:
Total score can range from 0-2
A score of 2 indicates high brand awareness, while a score of 0 indicates low brand awareness.
Brand Image:
Total score can range from -4 to +4
A score of +4 indicates a highly positive brand image, while a score of -4 indicates a highly negative brand image.
A score of 0 indicates a neutral brand image.
Brand Loyalty:
Total score can range from 0-4
A score of 4 indicates high brand loyalty, while a score of 0 indicates low brand loyalty.
Brand Equity:
Total score can range from 0-2
A score of 2 indicates high brand equity, while a score of 0 indicates low brand equity.
Overall Brand Perception:
To determine overall brand perception, add the scores from each sub-concept (Brand Awareness, Brand Image, Brand Loyalty, and Brand Equity).
Total score can range from -8 to +12
A score of +12 indicates a highly positive overall brand perception, while a score of -8 indicates a highly negative overall brand perception.
A score of 0 indicates a neutral overall brand perception.
Mindfulness has become an increasingly popular concept in recent years, as people strive to find ways to reduce stress, increase focus, and improve their overall wellbeing. One of the most widely used tools for measuring mindfulness is the Mindful Attention Awareness Scale (MAAS), developed by J. Brown and R. Ryan in 2003. In this blog post, we will explore the MAAS and its different scales to help you better understand how it can be used to measure mindfulness.
The MAAS is a 15-item scale designed to measure the extent to which individuals are able to maintain a non-judgmental and present-focused attention to their thoughts and sensations in daily life. The scale consists of statements that are rated on a six-point scale ranging from 1 (almost always) to 6 (almost never). Respondents are asked to indicate how frequently they have experienced each statement over the past week.
The MAAS is divided into three subscales, which can be used to measure different aspects of mindfulness. The first subscale is the Attention subscale, which measures the extent to which individuals are able to maintain their focus on the present moment. The second subscale is the Awareness subscale, which measures the extent to which individuals are able to notice their thoughts and sensations without judging them. The third subscale is the Acceptance subscale, which measures the extent to which individuals are able to accept their thoughts and feelings without trying to change them.
Each subscale of the MAAS consists of five items. Here are the items included in each subscale:
Attention Subscale:
I find myself doing things without paying attention.
I drive places on “automatic pilot” and then wonder why I went there.
I find myself easily distracted during tasks.
I tend not to notice feelings of physical tension or discomfort until they really grab my attention.
I rush through activities without being really attentive to them.
Awareness Subscale:
I could be experiencing some emotion and not be conscious of it until sometime later.
I break or spill things because of carelessness, not paying attention, or thinking of something else.
I find it difficult to stay focused on what’s happening in the present.
I find myself preoccupied with the future or the past.
I find myself listening to someone with one ear, doing something else at the same time.
Acceptance Subscale:
I tell myself that I shouldn’t be feeling the way that I’m feeling.
When I fail at something important to me I become consumed by feelings of inadequacy.
When I’m feeling down I tend to obsess and fixate on everything
Awareness Subscale:
I could be experiencing some emotion and not be conscious of it until sometime later.
I break or spill things because of carelessness, not paying attention, or thinking of something else.
I find it difficult to stay focused on what’s happening in the present.
I find myself preoccupied with the future or the past.
I find myself listening to someone with one ear, doing something else at the same time.
Acceptance Subscale:
I tell myself that I shouldn’t be feeling the way that I’m feeling.
When I fail at something important to me I become consumed by feelings of inadequacy.
When I’m feeling down I tend to obsess and fixate on everything
Validity is a fundamental concept in research, particularly in media studies, which involves analyzing various forms of media, such as film, television, print, and digital media. In media studies, validity refers to the extent to which a research method, data collection tool, or research finding accurately measures what it claims to measure or represents. In other words, validity measures the degree to which a research study is able to answer the research question or hypothesis it aims to address. This essay will explain the concept of validity in media studies and provide examples to illustrate its importance.
In media studies, validity can be divided into two types: internal validity and external validity. Internal validity refers to the accuracy and integrity of the research design, methodology, and data collection process. It concerns the extent to which a study can rule out alternative explanations for the findings. For example, in a study examining the effects of violent media on aggression, internal validity would be threatened if the study did not control for other variables that could explain the findings, such as prior aggression, exposure to other types of media, or social context.
External validity, on the other hand, refers to the generalizability of the findings beyond the specific research context. It concerns the extent to which the findings can be applied to other populations, settings, or conditions. For example, a study that examines the effects of social media on political participation may have high internal validity if it uses a rigorous research design, but if the study only includes a narrow sample of individuals, it may have low external validity, as the findings may not be applicable to other groups of people.
The concept of validity is essential in media studies, as it helps researchers ensure that their findings are accurate, reliable, and applicable to the real world. For instance, a study that examines the effects of advertising on consumer behavior must have high validity to make accurate conclusions about the relationship between advertising and consumer behavior. Validity is also crucial in media studies because of the potential social and cultural impact of media on individuals and society. If research findings are not valid, they may lead to incorrect or harmful conclusions that could influence media policy, regulation, and practice. To ensure the validity of research findings, media students should employ rigorous research designs and methods that control for alternative explanations and increase the generalizability of the findings. For example, they can use randomized controlled trials, longitudinal studies, or meta-analyses to minimize the effects of confounding variables and increase the precision of the findings. They can also use qualitative research methods, such as focus groups or interviews, to gather in-depth and nuanced data about media consumption and interpretation
Concepts and variables are two key terms that play a significant role in media studies. While the two terms may appear similar, they serve distinct purposes and meanings. Understanding the differences between concepts and variables is essential for media studies scholars and students. In this blog post, we will explore the distinctions between concepts and variables in the context of media studies.
Concepts:
Concepts are abstract ideas that help to classify and describe phenomena. They are essential in media studies as they help in creating an understanding of the objects of study. Concepts are used to develop mental models of media objects, to analyze and critique them. For example, concepts such as “representation” and “power” are used to describe and understand how media texts work (Kellner, 2015).
Variables:
Variables, on the other hand, are used to store data in a program or research. They are crucial in media studies research as they help in collecting and analyzing data. Variables are named containers that hold a specific value, such as numerical or textual data. Variables can be manipulated and changed during the research process. For example, variables such as age, gender, and socio-economic status can be used to collect data and analyze the relationship between media and society (Morgan & Shanahan, 2010).
Differences:
One of the significant differences between concepts and variables is that concepts are abstract while variables are concrete. Concepts are used to create mental models that help to understand and analyze media objects, while variables are used to collect and analyze data in research. Another difference is that concepts are broader and at a higher level than variables. Concepts are used to describe the overall structure and design of media texts, while variables are used to study specific aspects of media objects.
In addition, concepts are often used to group together related variables in media studies research. For example, the concept of “media effects” might be used to group variables such as exposure to media, attitude change, and behavior change. By grouping related variables together, researchers can have a better understanding of the complex relationships between variables and concepts in media studies research.
Concepts and Variables are two essential components of media studies research. Concepts help to develop mental models of media objects, while variables are used to collect and analyze data in research. By understanding the differences between these two terms, media studies scholars and students can create more effective and efficient research.
Type I and Type II errors are two statistical concepts that are highly relevant to the media industry. These errors refer to the mistakes that can be made when interpreting data, which can have significant consequences for media reporting and analysis.
Type I error, also known as a false positive, occurs when a researcher or analyst concludes that there is a statistically significant result, when in fact there is no such result. This error is commonly associated with over-interpreting data, and can lead to false or misleading conclusions being presented to the public. In the media industry, Type I errors can occur when journalists or media outlets report on studies or surveys that claim to have found a significant correlation or causation between two variables, but in reality, the relationship between those variables is weak or non-existent.
For example, a study may claim that there is a strong link between watching violent TV shows and aggressive behavior in children. If the study’s findings are not thoroughly scrutinized, media outlets may report on this correlation as if it is a causal relationship, potentially leading to a public outcry or calls for increased censorship of violent media. In reality, the study may have suffered from a Type I error, and the relationship between violent TV shows and aggressive behavior in children may be much weaker than initially suggested.
Type II error, also known as a false negative, occurs when a researcher or analyst fails to identify a statistically significant result, when in fact there is one. This error is commonly associated with under-interpreting data, and can lead to important findings being overlooked or dismissed. In the media industry, Type II errors can occur when journalists or media outlets fail to report on studies or surveys that have found significant correlations or causations between variables, potentially leading to important information being missed by the public.
An example of a Type II error in the media industry could be conducting a study on the impact of a certain type of advertising on consumer behavior, but failing to detect a statistically significant effect, even though there may be a true effect present in the population.
For instance, a media company may conduct a study to determine if their online ads are more effective than their TV ads in generating sales. The study finds no significant difference in sales generated by either type of ad. However, in reality, there may be a significant difference in sales generated by the two types of ads, but the sample size of the study was too small to detect this difference. This would be an example of a Type II error, as a significant effect exists in the population, but was not detected in the sample studied.
If the media company makes decisions based on the results of this study, such as reallocating their advertising budget away from TV ads and towards online ads, they may be making a mistake due to the failure to detect the true effect. This could lead to missed opportunities for revenue and reduced effectiveness of their advertising campaigns.
In summary, a Type II error in the media industry could occur when a study fails to detect a significant effect that is present in the population, leading to potential missed opportunities and incorrect decision-making.
To avoid Type I and Type II errors in the media industry, here are some suggestions:
Careful study design: It is important to carefully design studies or surveys in order to avoid Type I and Type II errors. This includes considering sample size, control variables, and statistical methods to be used.
Thorough data analysis: Thoroughly analyzing data is crucial in order to identify potential errors or biases. This can include using appropriate statistical methods and tests, as well as conducting sensitivity analyses to assess the robustness of findings.
Peer review: Having studies or reports peer-reviewed by experts in the field can help to identify potential errors or biases, and ensure that findings are accurate and reliable.
Transparency and replicability: Being transparent about study methods, data collection, and analysis can help to minimize the risk of errors or biases. It is also important to ensure that studies can be replicated by other researchers, as this can help to validate findings and identify potential errors.
Independent verification: Independent verification of findings can help to confirm the accuracy and validity of results. This can include having studies replicated by other researchers or having data analyzed by independent experts.
By following these suggestions, media professionals can help to minimize the risk of Type I and Type II errors in their reporting and analysis. This can help to ensure that the public is provided with accurate and reliable information, and that important decisions are made based on sound evidence
Transparency in research is a vital aspect of ensuring the validity and credibility of the findings. A transparent research process means that the research methods, data, and results are openly available to the public and can be easily replicated and verified by other researchers. In this section, we will elaborate on the different aspects that lead to transparency in research.
Research Design and Methods: Transparency in research begins with a clear and concise description of the research design and methods used. This includes stating the research question, objectives, and hypothesis, as well as the sampling techniques, data collection methods, and statistical analysis procedures. Researchers should also provide a detailed explanation of any potential limitations or biases in the study, including any sources of error.
Data Availability: One of the critical aspects of transparency in research is data availability. Providing access to the raw data used in the research allows other researchers to verify the findings and conduct further analysis on the data. Data sharing should be done in a secure and ethical manner, following relevant data protection laws and regulations. Open access to data can also facilitate transparency and accountability, promoting public trust in the research process.
Reporting of Findings: To ensure transparency, researchers should provide a clear and detailed report of their findings. This includes presenting the results in a way that is easy to understand, providing supporting evidence such as graphs, charts, and tables, and explaining any potential confounding variables or alternative explanations for the findings. A transparent reporting of findings also means acknowledging any limitations or weaknesses in the research process.
Conflicts of Interest: Transparency in research also requires that researchers disclose any conflicts of interest that may influence the research process or findings. This includes any funding sources, affiliations, or personal interests that may impact the research. Disclosing conflicts of interest maintains the credibility of the research and prevents any perception of bias.
Open Communication: Finally, researchers should engage in open and transparent communication with other researchers and the public. This includes sharing findings through open access publications and presenting findings at conferences and public events. Researchers should also be open to feedback and criticism, as this can help improve the quality of the research. Open communication also promotes accountability, transparency, and trust in the research process.
In conclusion, transparency in research is essential to ensure the validity and credibility of the findings. To achieve transparency, researchers should provide a clear description of the research design and methods, make data openly available, provide a detailed report of findings, disclose any conflicts of interest, and engage in open communication with others. Following these practices enhances the quality and impact of the research, promoting public trust in the research process.
Examples
Research Design and Methods: Example: A study on the impact of a new teaching method on student performance clearly states the research question, objectives, and hypothesis, as well as the sampling techniques, data collection methods, and statistical analysis procedures used. The researchers also explain any potential limitations or biases in the study, such as the limited sample size or potential confounding variables.
Data Availability: Example: A study on the effects of a new drug on a particular disease makes the raw data available to other researchers, including any code used to clean and analyze the data. The data is shared in a secure and ethical manner, following relevant data protection laws and regulations, and can be accessed through an online data repository.
Reporting of Findings: Example: A study on the relationship between social media use and mental health provides a clear and detailed report of the findings, presenting the results in a way that is easy to understand and providing supporting evidence such as graphs and tables. The researchers also explain any potential confounding variables or alternative explanations for the findings and acknowledge any limitations or weaknesses in the research process.
Conflicts of Interest: Example: A study on the safety of a new vaccine discloses that the research was funded by the vaccine manufacturer. The researchers acknowledge the potential for bias and take steps to ensure the validity and credibility of the findings, such as involving independent reviewers in the research process.
Open Communication: Example: A study on the effectiveness of a new cancer treatment presents the findings at a public conference, engaging in open and transparent communication with other researchers and the public. The researchers are open to feedback and criticism, responding to questions and concerns from the audience and taking steps to address any limitations or weaknesses in the research process. The findings are also published in an open access journal, promoting transparency and accountability.
You may read this TIP Sheet from start to finish before you begin your paper, or skip to the steps that are causing you the most grief.
1. Choosing a topic: Interest, information, and focus Your job will be more pleasant, and you will be more apt to retain information if you choose a topic that holds your interest. Even if a general topic is assigned (“Write about impacts of GMO crops on world food supply”), as much as possible find an approach that suits your interests. Your topic should be one on which you can find adequate information; you might need to do some preliminary research to determine this. Go to the Reader’s Guide to Periodical Literature in the reference section of the library, or to an electronic database such as Proquest or Wilson Web, and search for your topic. The Butte College Library Reference Librarians are more than happy to assist you at this (or any) stage of your research. Scan the results to see how much information has been published. Then, narrow your topic to manageable size:
Too Broad: Childhood diseases
Too Broad: Eating disorders
Focused: Juvenile Diabetes
Focused: Anorexia Nervosa
Once you have decided on a topic and determined that enough information is available, you are ready to proceed. At this point, however, if you are having difficulty finding adequate quality information, stop wasting your time; find another topic.
2. Preliminary reading & recordkeeping Gather some index cards or a small notebook and keep them with you as you read. First read a general article on your topic, for example from an encyclopedia. On an index card or in the notebook, record the author, article and/or book title, and all publication information in the correct format (MLA or APA, for example) specified by your instructor. (If you need to know what publication information is needed for the various types of sources, see a writing guide such as SF Writer.) On the index cards or in your notebook, write down information you want to use from each identified source, including page numbers. Use quotation marks on anything you copy exactly, so you can distinguish later between exact quotes and paraphrasing. (You will still attribute information you have quoted or paraphrased.)
Some students use a particular index card method throughout the process of researching and writing that allows them great flexibility in organizing and re-organizing as well as in keeping track of sources; others color-code or otherwise identify groups of facts. Use any method that works for you in later drafting your paper, but always start with good recordkeeping.
3. Organizing: Mind map or outline Based on your preliminary reading, draw up a working mind map or outline. Include any important, interesting, or provocative points, including your own ideas about the topic. A mind map is less linear and may even include questions you want to find answers to. Use the method that works best for you. The object is simply to group ideas in logically related groups. You may revise this mind map or outline at any time; it is much easier to reorganize a paper by crossing out or adding sections to a mind map or outline than it is to laboriously start over with the writing itself.
4. Formulating a thesis: Focus and craftsmanship Write a well defined, focused, three- to five-point thesis statement, but be prepared to revise it later if necessary. Take your time crafting this statement into one or two sentences, for it will control the direction and development of your entire paper.
For more on developing thesis statements, see the TIP Sheets “Developing a Thesis and Supporting Arguments” and “How to Structure an Essay.”
5. Researching: Facts and examples Now begin your heavy-duty research. Try the internet, electronic databases, reference books, newspaper articles, and books for a balance of sources. For each source, write down on an index card (or on a separate page of your notebook) the publication information you will need for your works cited (MLA) or bibliography (APA) page. Write important points, details, and examples, always distinguishing between direct quotes and paraphrasing. As you read, remember that an expert opinion is more valid than a general opinion, and for some topics (in science and history, for example), more recent research may be more valuable than older research. Avoid relying too heavily on internet sources, which vary widely in quality and authority and sometimes even disappear before you can complete your paper.
Never copy-and-paste from internet sources directly into any actual draft of your paper. For more information on plagiarism, obtain from the Butte College Student Services office a copy of the college’s policy on plagiarism, or attend the Critical Skills Plagiarism Workshop given each semester.
6. Rethinking: Matching mind map and thesis After you have read deeply and gathered plenty of information, expand or revise your working mind map or outline by adding information, explanations, and examples. Aim for balance in developing each of your main points (they should be spelled out in your thesis statement). Return to the library for additional information if it is needed to evenly develop these points, or revise your thesis statement to better reflect what you have learned or the direction your paper seems to have taken.
7. Drafting: Beginning in the middle Write the body of the paper, starting with the thesis statement and omitting for now the introduction (unless you already know exactly how to begin, but few writers do). Use supporting detail to logically and systematically validate your thesis statement. For now, omit the conclusion also.
For more on systematically developing a thesis statement, see TIP sheets “Developing a Thesis and Supporting Arguments” and “How to Structure an Essay.”
8. Revising: Organization and attribution Read, revise, and make sure that your ideas are clearly organized and that they support your thesis statement. Every single paragraph should have a single topic that is derived from the thesis statement. If any paragraph does not, take it out, or revise your thesis if you think it is warranted. Check that you have quoted and paraphrased accurately, and that you have acknowledged your sources even for your paraphrasing. Every single idea that did not come to you as a personal epiphany or as a result of your own methodical reasoning should be attributed to its owner.
For more on writing papers that stay on-topic, see the TIP Sheets “Developing a Thesis and Supporting Arguments” and “How to Structure an Essay.” For more on avoiding plagiarism, see the Butte College Student Services brochure, “Academic Honesty at Butte College,” or attend the Critical Skills Plagiarism Workshop given each semester.
9. Writing: Intro, conclusion, and citations Write the final draft. Add a one-paragraph introduction and a one-paragraph conclusion. Usually the thesis statement appears as the last sentence or two of the first, introductory paragraph. Make sure all citations appear in the correct format for the style (MLA, APA) you are using. The conclusion should not simply restate your thesis, but should refer to it. (For more on writing conclusions, see the TIP Sheet “How to Structure an Essay.”) Add a Works Cited (for MLA) or Bibliography (for APA) page.
10. Proofreading: Time and objectivity Time permitting, allow a few days to elapse between the time you finish writing your last draft and the time you begin to make final corrections. This “time out” will make you more perceptive, more objective, and more critical. On your final read, check for grammar, punctuation, correct word choice, adequate and smooth transitions, sentence structure, and sentence variety. For further proofreading strategies, see the TIP Sheet “Revising, Editing, and Proofreading.”
Sampling error is a statistical concept that occurs when a sample of a population is used to make inferences about the entire population, but the sample doesn’t accurately represent the population. This can happen due to a variety of reasons, such as the sample size being too small or the sampling method being biased. In this essay, I will explain sampling error to media students, provide examples, and discuss the effects it can have.
When conducting research in media studies, it’s essential to have a sample that accurately represents the population being studied. For example, if a media student is researching the viewing habits of teenagers in the United States, it’s important to ensure that the sample of teenagers used in the study is diverse enough to represent the larger population of all teenagers in the United States. If the sample isn’t representative of the population, the results of the study can be misleading, and the conclusions drawn from the study may not be accurate.
One of the most common types of sampling error is called selection bias. This occurs when the sample used in a study is not randomly selected from the population being studied, but instead is selected in a way that skews the results. For example, if a media student is conducting a study on the viewing habits of teenagers in the United States, but the sample is taken only from affluent suburbs, the results of the study may not be representative of all teenagers in the United States.
Another type of sampling error is called measurement bias. This occurs when the measurements used in the study are not accurate or precise enough to provide an accurate representation of the population being studied. For example, if a media student is conducting a study on the amount of time teenagers spend watching television, but the measurement tool used only asks about prime time viewing habits, the results of the study may not accurately represent the total amount of time teenagers spend watching television.
Sampling error can have a significant effect on the conclusions drawn from a study. If the sample used in a study is not representative of the population being studied, the results of the study may not accurately reflect the true state of the population. This can lead to incorrect conclusions being drawn from the study, which can have negative consequences. For example, if a media student conducts a study on the viewing habits of teenagers in the United States and concludes that they watch more reality TV shows than any other type of programming, but the sample used in the study was biased toward a particular demographic, such as affluent suburban teenagers, the conclusions drawn from the study may not accurately reflect the true viewing habits of all teenagers in the United States. Sampling error is a significant issue in media studies and can have a profound effect on the conclusions drawn from a study. Media students need to ensure that the samples used in their research are representative of the populations being studied and that the measurements used in their research are accurate and precise. By doing so, media students can ensure that their research accurately reflects the state of the populations being studied and that the conclusions drawn from their research are valid.