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Chapter 8 & 9 Notes

by: Lili Notetaker

Chapter 8 & 9 Notes 306

Lili Notetaker
Minnesota State University, Mankato
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Chapter 8 and 9 Notes. Evaluating Research and Hypothesis and Research Questions.
Research Methods
Deepa Oommen
Class Notes
hypothesis, Researchquestions, Evaluatingresearch, warrants




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This 7 page Class Notes was uploaded by Lili Notetaker on Thursday September 22, 2016. The Class Notes belongs to 306 at Minnesota State University - Mankato taught by Deepa Oommen in Fall 2016. Since its upload, it has received 33 views. For similar materials see Research Methods in (CMST) Communication Studies at Minnesota State University - Mankato.

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Date Created: 09/22/16
CHAPTER 8: EVALUATING RESEARCH  We try to evaluate things every day in life.  Key question: What does it mean to be reliable?  Research Warrants: Assurances of results. Let’s scholars show how their data/evidence reliably support their arguments or claims. SOCIAL SCIENTIFICRESEARCHWARRANTS: Social scientissfocus warrants of precision, power, parsimony, reliability and validity.  Precision: Your accuracy on measuring your variables.  Power: Multi-faceted concept. Two kinds: Conceptual power and Methodological power.  Conceptual power: Definitions are powerful when they provide broad or detailed insight about a concept.  Methodological power: It’s better for data selection procedures to be as representative of the population as possible. Samples allow more generalizations.  Parsimony: Combination of power and precision. Social scientists try to be detailed as possible.  Reliability: Your instrument should perform the same way over time and is the essence of reliability  Our measurements can never be 100% reliable, error is always involved.  Measurement errors = noise or threats to reliability. 3 main causes: 1.) Errors in data entry. 2.) Instrument confusion (some surveys can be hard to understand and therefore not effective) 3.) Random human differences (Humans are not perfect) 4 WAYS TODETERMINEMEASUREMENT RELIABILITY: 1.) Intercoder Reliability: Statistical analysis of how similar/different codes are in coding data. Measures include: percent agreement, Cohen’s Kappa (k), Spearman’s rho, Pearson’s correlation (r), Krippendorf’s alpha. 2.) Alternate Forms: Using two or more instruments to measure the same construct or trait. Purpose is to see how similar the scores of the participants are. 3.) Test-retest: Giving the same measure (s) to participants at multiple points in time. 4.) Internal Consistency (Homogeneity): The items in the measure having generally consistent responses from participants. VALIDITY: The extent to which the test measures what it is supposed to measure. Three kinds: Content, Construct, Criterion. 1.) Content Validity: Degree to which a scale, measure, and/or instrument measures all aspects of a behavior, trait or state. 2.) Construct Validity: Two parts. First: Construct must be understood & defined. Second: Usefulness in measuring construct must be established. 3.) Criterion-related Validity: A measure, scale, or instrument demonstrating effectiveness in predicting indicators or criterion of a construct. 2 Kinds:  Predictive Validity: When criterion is measured after test.  Concurrent Validity: When test scores are obtained at same time as criterion measures. INTERPRETIVERESEARCHWARRANTS: Smaller samples that are in-depth analyses of how groups or case studies understand the world.  Worthy Topic: Topic should be interesting, significant, timely & relevant.  Rigor: Steps must be taken to make sure research is done appropriately. .  Sincerity: How genuine & valuable you are as a researcher.  Credibility: How dependable & trusting you are at conveying realities expressed to you.  Thick Description: In-depth explanation. What you as the researcher experienced.  Triangulation: Using multiple data sets, various methods, various theories, various researchers to explore same phenomenon. .  Resonance: Using impactful cases or quotations to impact an audience. Various ways.  Transferability: Readers being able to transfer results of one study to another context in their life.  Aesthetic Merit: A piece of research that is artistically and imaginatively written that it affects the reader.  Significant Contribution: 4 Kinds for Interpretive Study. Does not need each contribution but at least one.  Theoretical: When the study develops, builds on , critiques or further explains theory.  Heuristic: Study piques the interest of readers and calls for further investigations into the same subject.  Methodological: Study could propose a new method of inquiry  Practical: Research offers advice to medical practitioners on best practices for better health outcome.  Ethical Manner: Informed consent, doing no harm, avoiding deception & guaranteeing privacy or confidentiality, all paradigms.  Coherence: Studies should achieve their stated purpose, accomplish what they need, use methods and representation practices, and attentively interconnect literature reviewed. Linking of methods with literature and argumentation. CRITICAL& CULTURAL RESEARCH WARRANTS: Some of same warrants as the interpretive paradigm. Critical theorists- draw broader conclusions about research. Skeptical of social scientific research methods.  Reflexivity: Solution for critical theorists. Idea that research must be accountable for itself. Practice of turning criticism back on itself. CHAPTER 9: HYPOTHESIS & RESEARCH QUESTIONS  Hypothesis-statements about the relationship between variables.  Research Questions-questions about proposed relationships between variables. TYPESOF HYPOTHESIS& RESEARCH QUESTIONS:  Research Question: Question that focuses on your study.  Hypotheses: Testable statement that 2 or more concepts or ideas are related or differ in some way. (Only in quantitative studies). Two Kinds:  Null Hypothesis: No relationship between variables. (ex: H0: There is no relationship btwn a student’s sex and college GPA)  Research Hypothesis: Difference or relationship exists. Comes in 3 forms. 1.) Non-directional hypothesis: There is a difference or relationship but doesn’t state in which direction or magnitude (ex: H1: There is a difference btwn the college GPAs of men & women or RQ1: Is there a diff. btwncollege GPAs of men & women?) 2) Directional hypothesis: There is a difference or relationship, does state the direction or magnitude (ex: H2: Female college students have higher college GPAs than male students or RQ2: Will female college students have higher GPAs than male students?) 3.) Casual hypothesis: Proposes a relationship btwn variables in which cause & effect relationship is expressed (ex: H3: The more education one has, the more money on will make in life or RQ3: Does educational level lead to increased monetary stability in life?) TYPESOF HYPOTHESIS& RESEARCH QUESTIONSTO USE?:  Testing a difference or relationship btwn varibluse a research hypothesis  Testing or exploring for differences or a relatonresearch hypothesis or research question HYPOTHESISAND RESEARCH QUESTION CHARACTERISTICS:  Good Hypothesis: 1.) Statement not question. 2.) Expected relationship btwnvariables. 3.) Based on literature. 4.) Not too long. 5.) Testable.  Good Research Question: 1.) Form of question. 2.) Tells focus of study 3.) Based on literature. 4.) Not too long. 5.) Must be something you can research. TESTING: st  1 step: Developing research idea.  Collect research (lit reviews).  Conduct research (collect/analyze data).  Consider errors(social scientific only).  Results and conclusions. ERROR:  Central Limit Theorem: Data taken from larger samples will tend to be more normally distributed. Statistical distributions can be symmetrical or asymmetrical.  Symmetrical: A single peak in the distribution at the mean, called a bell curve.  Asymmetrical: Skewed in some way. Scores are shifted to right/left of distribution centers.  Error: Every distribution will have error. Degree to which a sample differs from the population. CASE STUDY:  SD Standard Deviation: Average distance btwn a score and the mean. Larger SD=more variability in distribution. Smaller SD=less variability.  Symmetrical: A single peak in the distribution at the mean, called a bell curve.  Asymmetrical: Skewed in some way. Scores are shifted to right/left of distribution centers.  Confidence Interval: 95 percent rule. Expectation of accuracy is 95% and inaccuracy is 5%.  P ≥ .05 more than a 95% chance that null hyp. is true.  P ≤ .05 less than a 5% chance that null hyp. is true.  P ≤ .01, less than 1% chance that null hyp. is true.  P ≤ .001, less than .1% chance null hyp. is ture.


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