o
Major goal –
clarity
o
Remember that the goal
of your research is to communicate what you did, so you want to be as clear as
you can.
o
Avoid jargon when
possible, don’t be too creative, avoid slang and colloquialisms.
o
Avoid sexist language
o
Also try to be fairly
concise – don’t use a whole paragraph when two sentences will do
· Know the basic parts of a research article:
o
Title Page
§
Title, Authors,
Affiliation, Short title, running head
·
Abstract
o
100 to 120 words
o Introduction - gives you the background that you need and outline the issues, the theory, and the hypotheses
§ What is the author's goal?
§ What are the hypotheses?
§ If you had designed the experiment, how would YOU have done it?
o Method - tells the reader exactly what was done, with enough detail that the reader could actually replicate the study.
§ Is your method better than theirs?
§ Does the authors method actually test the hypotheses?
§ What are the independent, dependent, and control variables?
§ Based on what the authors did, what results do YOU expect?
o Results - gives a summary of the results and the statistical tests
§ Did the author get unexpected results?
§ How would you interpret the results?
§ What implications would YOU draw from these results?
o Discussion - the interpretation and implications of the results
§ Does YOUR interpretation or the authors' interpretation best represent the data?
§ Do you or the author draw the most sensible implications and conclusions?
· Using tables and graphs to present your results.
o How to make bar graphs and line graphs
o
How to make a table in
APA format
- Descriptive statistics are statistical procedures used to summarize, organize, and simplify data.
- Inferential statistics consist of techniques that allow us to study samples and then make generalizations about the populations from which they were selected.
Two
levels of our situations
Sampling error is the discrepancy or amount of error, that exists between a sample statistic and the corresponding population parameter.
Common Descriptive statistics of Distributions
There are 3 characteristics used that completely describe a distribution: shape, central tendency, and variability.
Shape:
Central tendency
Variability
Central Limit Theorem: The central limit theorem is an
important mathematical theorem for statistics. It tells us something important about the shape of the
distribution of sample means under certain conditions. Namely, if the sample size is large,
the distribution of sample means is normal. This allows us to determine probability values for sample
means (how likely the sample mean came from the population we know about).
Inferential statistics
Common statistical tests
Hypothesis testing is an inferential procedure that uses sample data to evaluate
the credibility of a hypothesis about a population.
type I error (a, alpha) - the H0 is actually correct, but the experimenter rejected it
type II error (b, beta)- the H0 is really wrong, but the experiment didn’t feel as though they could reject it
The alpha
level (a), or
level of significance,
Reporting statistical tests (including Symbols used)
Mean and Standard Deviation
Chi-Square
T Tests.
ANOVAs
Correlations
Regression
Why? And Basic features
- Doing ethical science
Institutional review board approval
Informed consent
Avoiding deception
Freedom from coercion
Protection from harm
Removing undesirable consequences
Debriefing .
*confidentiality
Costs vs. Benefits