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Data Collection

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HSCI 432 SFU FHS

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Data Collection

  1. 1. DATA COLLECTION HSCI 432: Seminar in Epidemiology Faculty of Health Sciences Simon Fraser University
  2. 2. LECTURE CONTENT • Survey Design • Survey Distribution Kiffer G. Card, PhD
  3. 3. PREPARING YOUR SURVEY | TYPES OF STUDIES • Not all research questions demand surveys. • Publicly Available Data • https://publichealth.jmir.org/2018/3/e61/ • http://dx.doi.org/10.2196/publichealth.8145 • Surveillance and Administrative Data • https://link.springer.com/article/10.1007%2Fs10461-017-1825-3 • Qualitative Data • Focus Groups and Interviews • Can allow a more nuanced insight into a research question • Can build rapport with participants, more personal • More effective for people for whom surveys may pose a challenge (e.g. non-native English speakers, individuals with dyslexia) The focus of this lecture
  4. 4. PREPARING YOUR SURVEY | RESEARCH QUESTIONS • A research question is the goal of a research project and aims to answer a specific question about your topic of interest. MATERNAL-CHILD HEALTH BREASTFEEDING • Are rural women in British Columbia more likely to breastfeed than urban women? • If so, are differences in breastfeeding between rural and urban women due to ethnicity, race, or indignity?
  5. 5. PREPARING YOUR SURVEY | RESEARCH QUESTIONS Focus the question Pick a question Ask some questions Narrow the topic Pick a topic • Follow these steps to ensure your research questions are well formulated: • Research questions should be justified by (a) the lack of previous research on the selected question, (b) the need to replicate previous findings, or (c) the need to reassess previous findings using new and approved methodology.
  6. 6. PREPARING YOUR SURVEY | RESEARCH QUESTIONS • Clear research questions also make it easier for you to collect and analyze data! “What factors are associated with HIV testing?” “Is increasing distance to nearest HIV testing facility associated with reduced likelihood with reduced likelihood of getting an HIV test in the past two years?” vs.
  7. 7. GROUP ACTIVITY • Step 1: Identify a research question related to opioid use. • Step 2: Develop a short questionnaire to answer this research question.
  8. 8. Descriptive Numeric Interval (Discrete) Ratio (Continuous)Nominal Ordinal Quantitative Data Numerical values without a true zero point, but equal spacing between values. Numerical values with a true zero point and with equal spacing between values. Categorical values without any numerical ranking. Categorical values that can be ranked but are not necessarily evenly spaced. Multilevel Dichotomous TYPES OF DATA
  9. 9. SURVEY QUESTIONS| WRITE WELL • Good questions start with proper: • Spelling • Grammar • Punctuation • Questions should be written at about a 6th grade reading level. • Avoid Jargon • Provide explanations for terms that are not well-known and their use is unavoidable. • Short and simple. • Make sure questions are direct and not vague.
  10. 10. SURVEY QUESTIONS| WRITE FOR UNDERSTANDING • When respondents do not understand the question or its purpose, they: • Drop out of the survey • Try to guess what the question is asking, and respond to that that • Select random answers. Good questions  good data Bad questions  bad data Extra, unnecessary cognitive effort  bad data!
  11. 11. SURVEY QUESTIONS| SURVEY TRANSLATIONS • Translating and adapting surveys for multiple languages includes: • Forward Translation • Aim for conceptual equivalencies with each question and not a word-for-word translation. • Expert Panel Back Translation • Bilingual expert panel should re-translate the version back into the first language and resolve any translation problems. • Pre-testing and cognitive interviewing • Systematic debriefing of pilot test-takers to confirm understanding of each question. • Final Version
  12. 12. SURVEY QUESTIONS| FIXED CHOICE QUESTIONS Are you not happy with the care you received from your doctor? Yes No Example
  13. 13. SURVEY QUESTIONS| FIXED CHOICE QUESTIONS • Easier data collection • Easier data analysis • Best approach for large populations • A variety of ways to ask questions • Must include all reasonable possibilities or you may not get at participant’s true feelings/thoughts PRO CONTRA
  14. 14. SURVEY QUESTIONS| FIXED CHOICE QUESTIONS • Tricks and Tips • Randomize order of choices for non-ordinal options to reduce bias. • Use a write-in box to allow users to provide “other” response options that you did not think of. • These will have to be either reclassified or treated as their own “miscellaneous” category • There is no such thing as an other. • You may want to include options for “non-applicable” and “refuse to answer.”
  15. 15. SURVEY QUESTIONS| REFUSE TO ANSWER • Under what circumstances would you want to include a “refuse to answer” option? • Under what circumstances would you NOT want to include a “refuse to answer” option? • In these instances how might you mitigate the risks associated with having people answer these questions?
  16. 16. • Open questions can be used to add depth or when there are too many variations in response. • When possible closed-ended questions should be used instead. SURVEY QUESTIONS| OPEN-ENDED QUESTIONS Tell us about your relationship with your primary care physician. Examples Enter Text Here What do you do for work? Enter Text Here Ensure boxes are adjustable or match the desired length.
  17. 17. SURVEY QUESTIONS| OPEN-ENDED QUESTIONS • Offers flexibility and freedom in responding • Rich, interesting data • Time-consuming • Coding a challenge • Vague or irrelevant responses PRO CONTRA
  18. 18. SURVEY QUESTIONS| CHECK ALL THAT APPLY • “Check all that apply” are used when multiple answers might be relevant to an individual. “Which of the following services are you interested in accessing? (Check all that apply) Elder (Indigenous) Knowledge Keeper (Indigenous) Psychiatrist Clinical Psychologist Registered Counsellor Peer counsellor/navigator Social worker Sex therapist / sexologist None of the above Example
  19. 19. SURVEY QUESTIONS| CHECK ALL THAT APPLY • Makes data collection easier for participants. • Its impossible to say whether a checkbox was left unclicked due to it not applying or due to a person skipping over and missing the option. PRO CONTRA
  20. 20. Example SURVEY QUESTIONS| MATRIX QUESTIONS Below is a list of ways you might have felt. How often have you felt this way during the past week? Bothered by things Loss of Appetite Hopeless Fearful Restless Lonely Rarely Sometimes Often
  21. 21. SURVEY QUESTIONS| MATRIX QUESTIONS • Items use the same scale • A time-saver for the researcher and respondent • Can save space • Can become visually overwhelming with too many prompts • Scale points must be identical PRO CONTRA
  22. 22. SURVEY QUESTIONS| MATRIX QUESTIONS Tips for making Matrix Questions • It doesn’t really matter what points you put at which ends of the scale – as long as you are consistent for every question. • Label every scale point! • How many scale points? • It depends on what you’re measuring and who you’re sampling. • Generally, 5-7 is recommended… • I find 4-5 to be adequate and 7 to be overwhelming. • Be sure the scale matches the question • If you ask, “Are you satisfied…” the scale points should reflect satisfaction.
  23. 23. SURVEY QUESTIONS| MATRIX QUESTIONS • Are your matrix questions walls of text? Example
  24. 24. SURVEY QUESTIONS| MATRIX QUESTIONS • Repeat your headers to visually break things up Example
  25. 25. SURVEY QUESTIONS| MATRIX QUESTIONS • Neutral options can be a “cop out” choice • If you want the respondent to state their opinion, do not give a neutral option! • Neutral options may be interpreted as “does not apply to me” • Give the respondent a “does not apply” option or program your survey so it only shows question to relevant participants
  26. 26. SURVEY AESTHETICS | QUESTION TYPES • Lots of other question formats… • fixed-choice, open-ended questions, check-all-that-apply, matrix questions are used most often • Don’t use too many question types in a single survey. Simplest way to encourage participation in a survey is to make it look simple!
  27. 27. SURVEY AESTHETICS | LENGTH • Survey length is important • Focus group: undergrads don’t want to spend more than 10-15 minutes doing • Can’t always control how long the survey is (topic-dependent) • But you can make sure each question MUST be on the survey • Delete duplicates or vague questions • Employ skip logic or display logic so respondents see only relevant items
  28. 28. SURVEY QUESTIONS| GATEWAY QUESTIONS • Use gateway questions to • make sure participants aren’t asked irrelevant questions. • prime participants to better recall and probe their experiences. • Organize your questions from General to Specific. • Skip and display logic not only improve survey aesthetics… • … they also help minimize data errors as well because people cannot answer questions that do not apply to them. Do you have a primary care physician? When was the last time you visited your primary care physician? What was the purpose of your visit?
  29. 29. SURVEY QUESTIONS| SKIP LOGIC • Instructions (either on paper or programmed) that direct a respondent to a particular question based on their answer to a previous item. Example 4. “Are you not happy with the care you received from your doctor?” Yes No [ Skip to Question 10]
  30. 30. SURVEY QUESTIONS| DISPLAY LOGIC • Programming your survey so that questions are displayed to respondents only if they meet a set of predetermined criteria. • Predetermined criteria may be: • Responses to one or more earlier items e.g., “If yes to Q1 and no to Q2 and yes to Q3: show Q4” (Can’t do this with skip logic!) • Data associated with your panel e.g. All freshmen see Q1, all sophomores see Q2, all juniors see Q3. • Randomization
  31. 31. SURVEY QUESTIONS| DISPLAY LOGIC Example 1. Were you wearing a shirt? Yes No 2. Were you wearing shoes? Yes No 3. Did you attempt to get service? Yes No 4. Were you denied service? Yes No Q4 displayed if • Q1 or Q2 = No; and • Q3 = Yes
  32. 32. SURVEY QUESTIONS| DISPLAY LOGIC • Display Logic in Database ID SHIRTS SHOES ATTEMPT DENIED 1 Yes Yes No 8888 2 No Yes Yes No 3 No No Yes No 4 Yes No No 8888 5 Yes No Yes Yes 6 Yes Yes Yes 8888 7 No No No 7777 9999 = Missing 8888 = Question not asked 7777 = Participant Selected “Refused” 6666 = Participant Selected “Don’t Know” 6666 = Participant failed to complete
  33. 33. SURVEY AESTHETICS | EVALUATING YOUR SURVEY • Look at the survey! Preview it on multiple devices. • A cluttered, busy survey = cognitive load = nonresponse Things to consider: • Do you have to scroll down or across on the average laptop screen? • Break up long pages into bite sized chunks. • More pages is ok – just use a “survey progress” bar. • Does the eye have to track horizontally across the entire screen to read an item? • List down, not across
  34. 34. SURVEY AESTHETICS | EVALUATING YOUR SURVEY • Always test your survey! (and test, and test again, and test some more) • Circulate it to friends/colleagues • If possible, pilot it with people from the population you plan to research • Does the survey make sense? • Can people understand what you’re asking? • Do the response options make sense? • Is the survey sufficiently transparent, or is the purpose unclear? • How do you feel about the survey process? • Do you feel like your responses are contributing to something?
  35. 35. SURVEY AESTHETICS | EVALUATING YOUR SURVEY • Are you measuring what you think you are measuring? • Validity in testing Will be covered more next week…but here’s an idea of what you should consider: • Face validity: what does the survey look like it’s measuring? • Construct validity: what is it actually measuring? • Content validity: does it represent all facets of the thing you are trying to measure? trying to measure?
  36. 36. SURVEY AESTHETICS | EVALUATING YOUR SURVEY • Does the survey look O.K.? • Are all the scales similar (highest rating is on the same side for all items)? • Is it overwhelming or cluttered anywhere? • For online surveys: • Does the skip logic and display logic work? • What does the data look like when it is downloaded? Is it easy to interpret and manipulate?
  37. 37. SURVEY QUESTIONS| UNNECESSARY QUESTIONS • Usually arise when you are collecting data that is “interesting” but not related to a research question. • Can also result from using gate questions without skip/display logic. Do you use condoms when having sex? Yes No How frequently do you use condoms during sex? Always Most of the time Some of the time Seldom Rarely Never Example
  38. 38. SURVEY QUESTIONS| ANNOYING QUESTIONS • Do you have bells and whistles in your survey? • e.g. sliders, heat maps, animations • Format your survey to avoid them (if at all possible) • They are distracting. • May not work on all devices. Example
  39. 39. SURVEY QUESTIONS| DOUBLE-BARRELED QUESTIONS • Ask about multiple things in a single question How satisfied are you with your doctor and nurse? Very Satisfied Somewhat Satisfied Somewhat Dissatisfied Very Dissatisfied Example
  40. 40. Are you not happy with the care you received from your doctor? Yes No Are you happy with the care you received from your doctor? Yes No Example SURVEY QUESTIONS| NEGATIVE FRAMES • Avoid use of double negative and negatively framed questions as these can be difficult for readers to understand.
  41. 41. SURVEY QUESTIONS| LEADING QUESTIONS Do you believe that Truvada is an effective way to prevent HIV? Yes No How would you rate the effectiveness of Truvada in preventing HIV? It is effective It is not effective. Example• Leading questions prompt or encourage one answer over another through subtle or direct coercion.
  42. 42. SURVEY QUESTIONS| LOADED QUESTIONS In the past six months have you had unsafe sex? Yes No In the past six months have you had sex without a condom? Yes No Example• Loaded questions include complex, unjustified assumptions that may not be interpreted universally.
  43. 43. SURVEY QUESTIONS| ABSOLUTIST QUESTIONS Do you always tell the truth? Yes No Do you agree with the following statement? “It is never okay to lie.” Yes No Example• Avoid questions that require participants to make absolutist claims.
  44. 44. Example SURVEY QUESTIONS| ASSUMING QUESTIONS • If you have topics that are require special knowledge or understanding, these should be described to the reader, if possible. Does Bill C-130 benefit your family? Yes No
  45. 45. SURVEY QUESTIONS| INSENSITIVE QUESTIONS What is your gender? Male Female Example• Make sure your questions are culturally appropriate to the audience answering them?
  46. 46. SURVEY QUESTIONS| INADEQUATE RESPONSES Example• Your response options should include all appropriate responses. • Open ended “other” options should be used sparingly, but as necessary. (Sometimes use even if data wont be). What is your gender? Male Female
  47. 47. SURVEY QUESTIONS| NON-EXCLUSIVE RESPONSES What is your relationship status? Married Divorced Single Widowed Example• Response options should not “overlap” • Each person should be only able to select 1 answer. What if I am widowed, but re- married? Divorced and now single?
  48. 48. SURVEY QUESTIONS| MIDDLE RESPONSE OPTIONS • Middle response options may be difficult to work with, especially if variables are going to be collapsed. • Sometimes it is better to make people “choose a side.” How likely do you feel it is that you will get HIV? Strongly Agree Agree Neither Agree Nor Disagree Disagree Strongly Disagree Example
  49. 49. SURVEY QUESTIONS| BALANCED SCALES How likely do you feel it is that you will get HIV? Very Likely Likely Somewhat likely Unlikely Very Unlikely Example• Scales should generally be balanced, with an equal number of options for both sides of the spectrum.
  50. 50. LIKERT ITEMS Agreement Strongly Agree Agree Slightly Agree Slightly Disagree Disagree Strongly Disagree Importance Very Important Moderately Important Somewhat Important Somewhat Unimportant Moderately Unimportant Very Unimportant Quality Very Good Good Acceptable Poor Very Poor Satisfaction Very Dissatisfied Moderately Dissatisfied Slightly Dissatisfied Slightly Satisfied Moderately Satisfied Very Satisfied Likelihood Definitively Very Likely Somewhat Likely Equally Likely Somewhat Unlikely Probably Unlikely Definitely Not
  51. 51. MEASURING FREQUENCIES AND PERIODS • https://kpilibrary.com/topics/measurement-frequencies-and-periods Frequency Always Very Frequently Frequently Occasionally Rarely Very Rarely Never Frequency Very Frequently Frequently Occasionally Rarely Very Rarely Never
  52. 52. SURVEY DESIGN | QUESTION ORDER • Randomize question order to reduce bias. • Sometimes randomizing “blocks” of questions can be useful to govern the overall flow of a questionnaire. • Start with exciting and interesting material not demographics. • If people are going to refer their friends to participate, make sure you finish with some interesting stuff as well. • If questions are really important, they should appear earlier, to avoid drop off.
  53. 53. GROUP ACTIVITY • Step 1: Identify any changes to your survey based on today’s lecture using “track changes” and/or “comments” in word. • Step 2: Email your questionnaire to kiffercard@gmail.com
  54. 54. SURVEY IMPLEMENTATION | INVITATIONS • Invitations to do the survey are a “first impression” • Saying the wrong thing can drive people away! • People like a personal touch – use this to your advantage • Paper or online surveys: Address each respondent by his/her name, if possible • In-person or phone surveys: Err on the side of being overly formal. “Sir”, “Ms.”, “Dr.”, etc.
  55. 55. SURVEY IMPLEMENTATION | INVITATIONS • People also like to feel special – use this to your advantage • “You have been selected…” • “We chose you for this project…” • “We hope you can share your opinion, we want to know what you think…” • Yes, it sounds cheesy, but consider the alternative. • “We sent this to everyone, and we are only really interested in averages.”
  56. 56. SURVEY IMPLEMENTATION | INVITATIONS • Include key information: • Survey aim • Time it takes to complete the survey (under 15 minutes is key!) • Deadline, if any • Incentive (more on this soon) • If using an online survey, don’t forget the link! • Keep it short! 1-2 paragraphs, tops.
  57. 57. SURVEY IMPLEMENTATION | DISTRIBUTION • Be thoughtful about when and how you distribute your survey • Consider the calendar: holidays, alumni giving cycles, exam periods, vacations • Survey fatigue – are other surveys circulating? • Sensitivity matters – consider the context. • A light-hearted survey about ice cream flavors should probably not be circulated the same day as a memorial service.
  58. 58. PREPARING YOUR SURVEY | DELIVERY METHODS • Computer Assisted Self-Interviews (CASI) • Online Administered Interviews • App-Administered Interviews • In-person • Interviews • Surveys • Phone • Random digit dialing • Mailers
  59. 59. DELIVERY METHODS | IN-PERSON SURVEYS • Researcher interacts directly with participant • Questions can be asked verbally or respondents can complete a paper / tablet survey. • Schedule Interview or solicit participation at a venue where qualified participants are likely to be found.
  60. 60. DELIVERY METHODS | IN-PERSON SURVEYS • Higher response rates • Decreases the number of “Don’t knows” and “No answers” • Can access hard-to-reach populations (e.g. senior citizens) • Can be done in a variety of settings • Can involve all 5 senses (e.g. taste test) • Researcher can make observations to enrich survey data • More expensive and time consuming • Interviewer error • Can be complex PRO CONTRA
  61. 61. DELIVERY METHODS | TELEPHONE SURVEYS • Interviewers ask the questions verbally over the phone, respondents’ answers are recorded (either digitally or manually).
  62. 62. DELIVERY METHODS | TELEPHONE SURVEYS • Higher response rates; decreases the number of “Don’t knows” and “No answers” • Lower cost and less time than in-person interviews • Can be computer-assisted • Unlisted numbers • Cell phones • Telemarketing ruined it for everyone PRO CONTRA
  63. 63. DELIVERY METHODS | MAILERS • Questionnaire is accompanied by a letter of explanation and a self-addressed, stamped envelope for returning the questionnaire • Follow-up mailing • Three mailings (1 original, 2 follow-ups) are the norm • Follow-up can be a postcard • 2-3 weeks in between mailings
  64. 64. DELIVERY METHODS | MAILERS • Large samples • Cheaper than interviews • Respondent does survey on own time • More expensive than online • Low response rates • Illegible answers! PRO CONTRA
  65. 65. DELIVERY METHODS | CASI • Potential respondents will • receive an email asking them to go to a web link where the survey resides • download an app where they can complete the survey • click a link advertised to them on a website • Options for design and administration vary according to platform
  66. 66. DELIVERY METHODS | ONLINE • Pros: • Good for sensitive topics • Can be distributed widely and publicly • Cons: • Potential for duplicated data • Includes both accidental and deliberate duplication • Pros • Tracks responses, can target reminders more effectively • Cons • Data security Anonymous Links Survey Panels
  67. 67. DELIVERY METHODS | MAILERS • Inexpensive, least time-consuming • Automatic data entry • Can easily merge with additional data • Can easily deploy skip/display logic • Able to force responses • Lower response rates than in-person • Respondents must have access to computer • Technical errors • Multiple responses trying to “game the system” for incentives. PRO CONTRA
  68. 68. MANAGING YOUR SURVEY | RESPONSE RATES • A high response rate… • Improve representativeness of sample • Provides more diverse opinions, better data • Protects against nonresponse error • A low response rate… • May or may not be bad • If the respondents are similar to the sample and population, maybe it’s ok
  69. 69. MANAGING YOUR SURVEY | RESPONSE RATES • What is a good response rate? • What is your expected response rate? • Depends on the survey, the population, and the incentive • In-person = highest response rate • 20%-35% for a 10-minute online survey • Be realistic, don’t over-promise
  70. 70. MANAGING YOUR SURVEY | RESPONSE RATES • Incentives increase response rates • Which incentives work best? • It depends on… • Your population • Your budget • Your survey methods • Guaranteed small incentives > Raffles • Be creative • Does not have to be expensive or flashy
  71. 71. MANAGING YOUR SURVEY | REMINDERS • Reminders • Participation drops steeply after a few days for online surveys • Usually after just 48 hours! • Online surveys: • Can email reminders…but be careful about duplicates • Reminders are easier when using survey panels • Mail surveys • Send postcards or new copies of survey • Keep track of returned mail • Depending on population, may wish to phone potential respondents to see if they need help
  72. 72. MANAGING YOUR SURVEY | REMINDERS 0 200 400 600 800 1000 1200 Number of Survey Responses Collected Reminder Issued
  73. 73. MANAGING DATA | RESPONSES -> DATA • Create a data dictionary • What are the variable names? What are the values? • Online surveys: • Deactivate!! • Download data into Excel, SPSS, SAS, etc. • Paper-and-pencil surveys: • Enter data in Excel, SPSS, SAS, etc. by hand • Double-entering data will help you catch errors with data entry, even if more time consuming
  74. 74. MANAGING DATA | DATA CLEANING • Clean your data… • Run descriptive statistics to… • Identify impossible values • How many hours of community service? 10,000,000 hours… • Look for outliers in the data • How much student debt? Most respondents report $50,000, but a few report $200,000… not impossible. • Look for patterns that may indicate errors • Maybe skip logic was faulty or coding was not correct?
  75. 75. MANAGING DATA | DATA CLEANING • Clean your data… • Identify duplicated data (e.g. two entries from same person) • Remove people who clicked through the survey, provided no usable data • Transform your data for statistical analysis • Recoding variables • Reducing data from multiple items into composite scores • Other statistical transformations, depending on analyses you intend to conduct
  76. 76. MANAGING DATA | DATA CLEANING • Clean your data… …but ALWAYS keep your original data saved! (You never know what you’ll need later!)
  77. 77. MANAGING DATA | MISSING DATA • Most surveys will have missing data somewhere • Respondents do not answer question • Question voluntarily or accidentally skipped • Question not shown to/asked of respondent • Respondents provide data, but it is bad data • How many hours of community service? 10,000,000… • Respondents discontinue survey • Survey attrition: can look at patterns to figure out if there is a “trigger” – perhaps a confusing question or overwhelming page…
  78. 78. MANAGING DATA | MISSING DATA • Missing data can be very harmful • Can contribute to nonresponse error • Those who answer questions are different than those who do not… • …and ultimately poor decision-making.
  79. 79. MANAGING DATA | MISSING DATA • First, examine patterns of missing data • Is the missing data random? Or is there a pattern of any kind? • Are some questions routinely skipped? (e.g., question asking students to evaluate a service that is rarely used) • Do many respondents drop out of the survey after or before the same item? • Do some kinds of respondents routinely skip some questions? (e.g., men don’t answer questions about the women’s center) • Sort your data to explore patterns of missing data more carefully
  80. 80. MANAGING DATA | MISSING DATA • There may be reasons why… • Two-sided paper survey • Very sensitive question, people don’t want to answer • Question is not relevant to respondent in ways you hadn’t previously considered • Question or survey instructions are unclear • Online survey not programmed correctly • …and sometimes, it’s just random.
  81. 81. MANAGING DATA | MISSING DATA • Decide what you want to do about missing data • This will largely depend on the data and how you plan to analyze it • Common approaches • Listwise deletion – delete the entire row of data • Decreases statistical power in reporting • Leave blank – but report your n for the item • Enter the survey average for the item • Enter a random value
  82. 82. MANAGING DATA | MISSING DATA • Analytic strategy (statistics) will depend on… …your research question …your data …the recipient of analysis …your statistical expertise …your expertise with relevant statistical software (SPSS is Tufts’ tool of choice) Don’t be afraid to ask for help – the wrong statistical approach can lead to the wrong conclusions.
  83. 83. REMINDERS • Next week we will discuss more about instrumentation. • Midterm in two weeks. • Make sure you’re keeping up on audio-readings. • In three weeks, you will have time to develop/refine your fellowship applications. • Pick groups of two or three and work out a plan for how you want to use this time. • Review the rubric and identify ways you can help each other. • Take advantage of a second set of eyes. • Actually use this time to begin thinking through some of the aspects of your proposal. • After the midterm, we will begin the analysis section of the course. It is highly recommended that you take a few afternoons over the next week to complete an R tutorial.
  84. 84. REMINDERS • Step 1: Go to the databases.lib.sfu.ca. • Step 2: Go to the “L” section. • Step 3: Scroll to “Lynda.com Online Training Library” • Step 4: Click “Connect” • Step 5: Select “Login to Lynda.com” • Step 6: Go to the search bar and type “R Statistics Essential Training.” • Step 7: Select the course by Barton Poulson. • Step 8: Enjoy the videos courtesy of the SFU library!

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