Attention to answer choices that result in double

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attention to answer choices that result in double negatives and avoid Bad: I would never cheat on an examination under any circumstance. Good: I would cheat on an examination under certain circumstances. 9. Avoid biased items and terms: 2 problems here 1. Leading the respondent to a particular choice (terrible) 2. Leading (most) respondents to guess your hypothesis (or agenda) if you have one Bad:specific questions of certain situations. Good: ask a general question about it In focus: likert scales -a set of response choices following a question stem that have been carefully arranged to accomplish the following two things: Range: answers cover the full range from negative to positive. Balance:: equal strength among negative and positive responses -likert scales use 5 categories (use any odd #, but it doesn’t get the name Likert, then) -The answer choices span the range of the underlying variable and are balanced Example: Not likert: How is your day going today?(awesome, okay, meh, awful) Likert: Rate your agreement with this statement: I’m having an awesome day. (strongly agree, agree, neutral, disagree, strongly disagree) The difference: imagine 2 people trying to answer question 1 both pick okay (their choices are subjective and unbalanced, as opposed to the likert scale) In focus: what to do about non-response: Missing data/missing cases: -Are a nearly universal feature of surveys and polls -are all too seldom discussed outside the academic world -can only be ignored when they are missing at random -that is, when the reasons for non-response have nothing at all to do with the questionnaire, the mode of collection, the questions, the topic, the surveyor’s appearance, the respondent’s individual attitudes -- anything at all that could lead to non-random non-response -if you can argue that your missing data are MAR, you can then safely exclude them from statistical calculations without biasing the results-- otherwise, NO!
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-the take-away: be ready for missing data and non-response (because you’ll have it in any poll) -If they don’t believe the evidence, they’ll reject the reasons, and with them the claim (Booth et al. (2008:130) Organizing “data” for your research report: Booth et al. make a crucial distinction -Reason- the logic-based explanation for why a claim should be accepted -evidence- the observation-based support for why a reason should be accepted evidence=data Outline form or storyboard(evidence in boxes?) 3 options: Organizing secondary source reports (and therefore how to evaluate their quality) Organizing and working with others’ data (and therefore how to evaluate its quality) Organizing and conducting your own (very basic) primary research For each source of evidence and data: ASK: on what basis will I trust, and expect my readers to trust my data?
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