2. But! Let’s first review…

3. Statistics: Describing/organizing data
DEPENDENT VARIABLE
INDEPENDENT VARIABLE

4. Measures of Central Tendency
Single score to represent a whole set
Mode
Mean
Median
Purpose: to summarize data, tell the story

5. Skews The mean has been biased in some way
Skews can change the story if any measure of central tendency is manipulated inappropriately
(draw skews from backboard)

6. Measures of Variation Examine data for validity/reliability Range –
Averages with low variability are more reliable than those with high variability
Range –
Standard deviation -
Range – gap between lowest and highest score
Standard deviation – how much scores deviate from one another to prove reliability

9. What % of a normal curve falls below the median?
50%

10. Making Inferences – so what do we do with it?
When averages from 2 samples are each reliable, then their differences are also reliable
Example: aggression in men vs. women
When averages are reliable, and when the two differences are also reliable, we find them statistically significant
Statistical significance – the outcome was not likely due to chance (eliminates extraneous/confounding variables)

11. Statistical Significance
Whenever we find something statistically significant, we are saying that the outcome was not likely due to chance
Is this a good or bad thing for validity or reliability in our experiment?

12. P-scores/P-values P-scores/p-values Null Hypothesis:
Based in how similar the samples were in regard to the dependent variable
Numerical values?
Null Hypothesis:
If the null hypothesis is found to be true, then in our experiment, the independent variable did not impact the dependent variable
What did impact the dependent variable?
Not opposite of testing hypothesis
p value
The reason for calculating an inferential statistic is to get a p value (p = probability). The p value is the probability that the samples are from the same population with regard to the dependent variable (outcome). Usually, the hypothesis we are testing is that the samples (groups) differ on the outcome. The p value is directly related to the null hypothesis.
The p value determines whether or not we reject the null hypothesis. We use it to estimate whether or not we think the null hypothesis is true. The p value provides an estimate of how often we would get the obtained result by chance, if in fact the null hypothesis were true.
If the p value is small, reject the null hypothesis and accept that the samples are truly different with regard to the outcome.
If the p value is large, accept the null hypothesis and conclude that the treatment or the predictor variable had no effect on the outcome.

13. The dependent variable in this study is the
A researcher studying the effect of noise level on concentration randomly assigns student participants to either a noisy room or a quiet room to take a problem solving test. The researcher subsequently compares the two groups’ test scores using a t-test and concludes that p = .05
The dependent variable in this study is the
a. p value
b. noise level
c. problem solving test scores
d. t-test
e. experimental group
The independent variable in this study is the
a. p value
3. In finding this experiment to be statistically significant, we can determine that
a. a type – II error exists
b. we accept the null hypothesis
c. we reject the null hypothesis
d. there is a 95% chance the outcome of the experiment occurred due to chance
e. there are no extraneous variables present C b c

14. Experimenter bias #1 confounding variable in experiments
So how do we do we control this bias?
Use a double blind procedure
Neither the experimenter nor the subjects know who is in the experimental group and who is in the control group
A “blind” procedure is just the subjects being unaware

15. Placebo effect
Placebos are fake variables, so that subjects don’t know which group they’re in
Always used in drug studies, where there’s a fake pill thrown in to control the study (usually a sugar pill)
Placebo effect: as many as 30% of subjects that receive a placebo report that they get better

16. Power of belief
View video clips