Introduction to Designing Experiments
"Adam suspects that most hairy dogs have balding owners. Testing his "pet" theory at a local park, he quickly finds flaws in his own experiment. This video demonstrates Adam's second test, involving better preparation, more rigorous analysis, and an exciting pasta cook-off. Showing how Adam can effectively determine the best spaghetti recipe, the program illustrates concepts that are central to the scientific method-including null, alternative, and two-tailed hypotheses; field and lab settings; sampling; primacy/recency effects; constant/random errors; and other testing principles. Graphic screens reinforce each concept and enable students to fully absorb the testing process."
- Experiment research and design (03:03)
- Hypotheses : null hypothesis, alternative hypothesis, two-tailed hypothesis (04:25)
- Selecting a sample (02:56)
- Experiment environments : natural or artificial (03:43)
- Quantitative data rejects null hypothesis (03:10)
- Error and bias : confounding variables (03:13)
- Debriefing participants (01:17)
"This video focuses on effective ways to understand and organize data using descriptive statistics. Analyzing data collected from studies of young music students, the video helps viewers sort through basic data-interpretation concepts: measures of central tendency, levels of measurement, measures of dispersion, and graphs. A wide range of organization principles are covered, including mode, median, and mean; discrete and continuous data; nominal, ordinal, interval, and ratio data; standard deviation; and normal distribution. Animation and graphics clarify and reinforce each concept. The video concludes with a quick quiz to assess understanding and focus on key areas."
- Scientific experiments : cause and effect (01:18)
- Generalizability, reliability, and validity (03:13)
- Measures of central tendency : mode, median, and mean (03:21)
- Levels of measurement : nominal, ordinal, and interval (05:57)
- Measures of dispersion : range and standard deviation (07:50)
- Graphs : normal distributions (06:23)
- Discrete data : bar chart, pie chart, histogram (03:23)
- Continuous data : line graphs and skewed distributions (01:44)
- Quantitative data quiz (02:31)
"Who said statistics were boring? Using magic and circus motifs, this program demonstrates the significance of probability theory and the importance of using the correct test to analyze research data. Host Amy and her friend Matt the Magician guide viewers through the need to make probability statements, and along with a team of students, use juggling skills to explore choice of test. Setting significance levels, tests of difference, the sign test, degrees of freedom, Yates correction, expected frequencies, parametric tests, and plastic interval scales are explored. Supporting graphics and animation enliven each discussion point and set up questions posed to viewers."
- Statistics : probability and certainty (05:29)
- Statistics : probability and prediction (03:53)
- Statistics : errors (01:05)
- Statistics : levels of significance (02:08)
- Tests of difference (04:00)
- Parametric tests (01:41)
- Binomial sign test (06:01)
- Statistical significance (03:30)
- Statistics : Wilcoxon signed-ranks test (02:43)
- Statistics : t-test (04:03)
"A dream may be the most difficult human experience to quantify-but dreaming is an excellent topic for building qualitative research skills. This program illustrates experiments, designed and conducted by students, that revolve around sleep and dreams. In the process, it provides thorough insight into the issues relevant to collecting and utilizing qualitative data. Viewers are shown how to create effective questionnaires, prepare participant interviews, assemble case studies, and conduct observational studies. The program also covers the use of content analysis and explores the correlational method, employed to make qualitative data more meaningful."
- Advantages and disadvantages of qualitative methods (04:42)
- Questionnaire method (08:47)
- Interview method (06:38)
- Observational method (05:44)
- Case study method (04:15)
- Content analysis (04:58)
- Correlational method (06:51)
- Value of qualitative methods (01:21)
(2017, 26 minutes)
"Dr. Allyson Holbrook discusses questionnaire design and survey research methods. Questionnaire design is important to survey research because small changes on the questionnaire can change the responses. Holbrook discusses survey research, her research on question wording, and the developments in the field."
Segments (2-5 minutes each):
- How are surveys used in social science research? What kinds of questions are survey methods most appropriate for?
- Why is the questionnaire design so important?
- What are the different types of questions you can ask in a survey?
- What are the types of constructs that can be measured with survey questions?
- Your research has tested the effect of question wording on answers to survey questions. What have you found?
- What are some of the problems associated with agree-disagree questions?
- When is it appropriate to use agree-disagree questions and when is it more appropriate to consider using a different format?
- Your research is also focused on developing methods to increase the honesty of respondents' answers to sensitive questions in surveys. What have you found?
- What key piece of advice do you have for survey researchers on questionnaire design or any aspect of survey methodology?
- Whose work has inspired you?
- What are the most exciting developments in the field of survey methods?
Segments of Allyson Holbrook Discusses Questionnaire Design
Segment 1 of "Allyson Holbrook Discusses Questionnaire Design" (2017, 3 minutes)
Segment 2 of "Allyson Holbrook Discusses Questionnaire Design" (2017, 3 minutes)