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Research Methods & Statistics:

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Presentation on theme: "Research Methods & Statistics:"— Presentation transcript:

1 Research Methods & Statistics:
“Those who trust in their own wits are fools”. -Proverbs 28:26

2 Guiding Principles The goal is research literacy.
Most of us will not be career researchers. BUT….we are all consumers of research. How do you tell the good from the bad? No research is perfect. Everything is open to critique—a great platform for critical thinking.

3 Methods Is Like Whac-A-Mole…
a fun game for which there is no perfect solution

4 Whac-A-Mole If I’m conducting my own research, the goal is to minimize the moles. If I’m considering the research of others, the goal is to identify as many moles as I can.

5 98% Certainty Answer the questions on the next slide by writing a small number and a large number such that you are at least 98% certain that the correct answer is in between.

6 98% Certainty The area of the US in square miles?
The population of Australia 2007? American battle deaths in Spanish-American War? Female psychiatrists in the US in 2005? Operating nuclear plants worldwide in 2007?

7 98% Certainty Area of US: Australian pop.: Battle deaths:
Female psychiatrists: Nuclear plants: 3.6 million sq. miles 20.4 million 385 13,079 435 How’d that work out?

8 Topic 1: Moles Hindsight bias (Myers Activity)
Confirmation bias (NY Times activity) Overconfidence

9 Topic 2: Descriptive Techniques
Case studies Surveys Naturalistic observation.

10 Case Studies Case Study- Descriptive technique in which one individual or group is studied in depth in the hope that a universal principle will be discovered. What is the potential mole? The person or group studied may be atypical. Individual cases are useful, but can often lead to mistaken judgments, and false conclusions.

11 Phineas Gage https://www.youtube.com/watch?v=_nikOxNfjqs
Most famous psychological case study. Taught psychologists a lot about the brain.

12 Survey Activity Half of you will go out in the hall while the other half answers the questions on the next slide. When they are finished, the other half of you will come in and answer questions on the following slide.

13 Group 1 Is the Mississippi River longer or shorter than 500 miles?
2. How many miles long is it?

14 Group 2 Is the Mississippi River longer or shorter than 3000 miles?
2. How many miles long is it?

15 Activity Continued Both of the groups actually answered the same second question. It was clearly an unambiguous question, no tricks or anything. Let’s record the answers to the second question from the first group, and then the answers for the second group. What do we notice? *The river is 2,320 miles long

16 Surveys A survey- a technique for ascertaining the self-reported attitudes and behaviors of a particular group, usually by questioning a representative, random sample of the group. What are the potential moles? The wording of the question can influence the answer. How do you insure the sample is indeed random, and accurately reflects the attitudes of the group as a whole?

17 Good Surveying Techniques
Carefully word your survey questions in order to ensure you are not generating a particular response. Control for any errors by asking a similar question with different wording. Avoid sampling bias or a flawed sampling process that produces an unrepresentative sample. Establish a random sample i.e. a sample that fairly represents a population because each member has an equal chance of inclusion.

18 Topic 3: Experimentation
The purpose of an experiment is to establish a cause-and-effect relationship. Experiments are the only research method that can establish cause-and-effect.

19 Example Experiment General hypothesis: Food affects learning.
Specific hypothesis with operational variables: Students who eat an oatmeal raisin cookie before class each day will have higher average scores on the semester final than students who don’t eat a cookie.

20 Eating cookies before class each day will lead to higher average scores.
Variables: Independent (IV) Controlled by experimenter The “cause” variable Dependent (DV) Predicted by experimenter The “effect” variable

21 Eating cookies before class each day will lead to higher average scores.
What if kids get cookies and A’s? Groups (conditions): to establish different levels of the IV Experimental group Exposed to IV Get cookie Control group Not exposed to IV No cookie

22 Eating cookies before class each day will lead to higher average scores.
Confounding Variables IV DV Environmental Expt. Gp. Cookie 95% Expectations Cntrl. Gp. No Cookie 82% Individual differences

23 Control for confounding variables
Environmental: Make the environment the same for both groups (so it’s not a variable). Expectations: Utilize a blind procedure (so nobody knows what to expect). Individual differences: Randomly assign participants to groups (so the differences have the same average impact on each group).

24 Random Sampling & Random Assignment
To select participants from population Allows you generalize results Random Assignment To divide participants into groups Controls individual difference confounding variables

25 Eating cookies before class each day will lead to higher average scores.
IV DV Expt. Gp. Cookie 95% Cntrl. Gp. No Cookie 82% 85% 93%

26 Statistical Significance
p value likelihood a result is caused by chance can be no greater than 5% p ≤ .05

27 Replication Non-replicated results are preliminary.
Linus Pauling (1970). Vitamin C prevents colds. IV DV Has never been proven, even after 16 double blind tests. Expt. Gp. Vit C Expt. Gp. 45% Fewer colds Cntrl. Gp. Placebo

28 Importance of Operational Definitions
Students are more likely to smile for their senior pictures if they have a friendly photographer. IV? Photographer friendliness DV? Smiling Operational definitions are needed for both of these variables. To illustrate the importance of this, have students determine how many of the students on the following slide are smiling.

29 How Many Smiles

30 Importance of Operational Definitions
If we want to be critical consumers of research, we need to always ask how research variables were operationalized (“What do they mean by ‘best school,’ ‘learning,’ ‘happiness,’ etc.?”). Research cannot be replicated without operational definitions.

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