Talks & Statistics (wrapping up)

Psych 231: Research Methods in Psychology

Announcements

Class experiment final draft papers due today Please make sure that your GA’s name is on it

Your posters (our checklist)

Content Introduction

• Problem of interest• Very brief summary of

past research• Basic purpose of

experiment(s)• Hypotheses

Method• Brief but clear• Design• Materials• Procedure (brief)

Results• Descriptive statistics• Inferential results

Tables and figures• Useful info to reader• Easy to understand

Discussion• Hypothesis rejected or

supported• Implication of results• A few take home points

References

Your posters (our checklist)

Format Overall clarity Organization Font size Figure/text balance Title Authors

Different kinds of talks

Research Presentations (typically 10 to 30 mins)

Paper with respondent Panel Presentation Workshop

Talk Content

Create a logical progression to the talk Hourglass shape Work on the transitions between slides

Be brief, but include enough details so that the audience can follow the arguments Use slides to help simplify/clarify points

• Include tables, graphs, pictures, etc. • Don’t just read the slides• but do “walk through” those that need it (e.g. graphs of

results) Be careful of jargon, explain terms (if in fact you

really need them)

Presentation of the talk

Make it smooth (lots of practice will help) Watch your speaking rate (again, practice) Maintain eye contact with whole audience Emphasize the key points, make sure that the

audience can identify these Point to the slides if it helps Beware jokes, can be a double-edged sword Don’t go over your time

Dealing with questions

Repeat the question in your own words so that the rest of the audience can hear it to make sure that you understood the question to buy yourself some time to think about the answer

Try not to be nervous you know your study better than anyone else

When preparing, try to think of likely questions and

prepare answers

Checklist for the talk

Preparation Analyze the audience Choose your main points

etc.

Prepare the Final Outline fix any problems/loose ends

Construct your “speaking” outline e.g., the note cards that you’ll read

Rehearse, rehearse, rehearse

Some inferential statistical tests

1 factor with two groups T-tests

• Between groups: 2-independent samples

• Within groups: Repeated measures samples (matched, related)

1 factor with more than two groups Analysis of Variance (ANOVA) (either between groups or

repeated measures)

Multi-factorial Factorial ANOVA

Some inferential statistical tests

1 factor with two groups T-tests

• Between groups: 2-independent samples

• Within groups: Repeated measures samples (matched, related)

1 factor with more than two groups Analysis of Variance (ANOVA) (either between groups or

repeated measures)

Multi-factorial Factorial ANOVA

Analysis of Variance

More than two groups Now we can’t just compute a simple difference score since

there are more than one difference

So we use variance instead of simply the difference• Variance is essentially an average difference

Observed variance

Variance from chanceF-ratio =

Lot’s of degree’s of freedom to keep track of• Overall df, df for numerator, df for denominator

1 factor ANOVA

1 Factor, with more than two levels Now we can’t just compute a simple difference score since

there are more than one difference• A - B, B - C, & A - C

XBXA XC

1 factor ANOVA

Null hypothesis: H0: all the groups are equal

XA = XB = XC

Alternative hypotheses

HA: not all the groups are equal

XA ≠ XB ≠ XC XA ≠ XB = XC

XA = XB ≠ XC XA = XC ≠ XB

The ANOVA tests this one!!

Do further tests to pick between these

XBXA XC

1 factor ANOVA

Planned contrasts and post-hoc tests:

- Further tests used to rule out the different Alternative

hypothesesXA ≠ XB ≠ XC

XA ≠ XB = XC

XA = XB ≠ XC

XA = XC ≠ XB

Test 1: A ≠ B

Test 2: A ≠ C

Test 3: B = C

Reporting your results The observed differences Kind of test Computed F-ratio Degrees of freedom for the test The “p-value” of the test Any post-hoc or planned comparison results

“The mean score of Group A was 12, Group B was 25, and Group C was 27. A 1-way ANOVA was conducted and the results yielded a significant difference, F(2,25) = 5.67, p < 0.05. Post hoc tests revealed that the differences between groups A and B and A and C were statistically reliable (respectively t(1) = 5.67, p < 0.05 & t(1) = 6.02, p <0.05). Groups B and C did not differ significantly from one another”

1 factor ANOVA

Factorial ANOVAs

We covered much of this in our experimental design lecture More than one factor

Factors may be within or between Overall design may be entirely within, entirely between, or mixed

Many F-ratios may be computed An F-ratio is computed to test the main effect of each factor An F-ratio is computed to test each of the potential interactions

between the factors

Factorial ANOVAs

Reporting your results The observed differences

• Because there may be a lot of these, may present them in a table instead of directly in the text

Kind of design• e.g. “2 x 2 completely between factorial design”

Computed F-ratios• May see separate paragraphs for each factor, and for interactions

Degrees of freedom for the test• Each F-ratio will have its own set of df’s

The “p-value” of the test• May want to just say “all tests were tested with an alpha level of

0.05” Any post-hoc or planned comparison results

• Typically only the theoretically interesting comparisons are presented