PSYC 220 FINAL Flashcards
(147 cards)
Numerical order for 1st row of counterbalancing
1, 2, n, 3, n-1, 4, n-2, 5, etc.
How to calculate for the largest number of people that can be used?
Divide number of subjects/levels into number of participants given in the problem and then multiply the answer by the number of subjects
Quasi-experiments
do not have to assign participants to levels, they already come in with those levels
How to write null hypothesis
“The mean”….”DV”……“participants”….”levels of experiment”…“WILL BE EQUAL.”
How to write out alternate hypothesis
“The mean”….”DV”……“participants”….”levels of experiment”…“WILL NOT BE EQUAL.”
How to write out interaction statement after writing down null/alternate hypothesis
The interaction between Level1 and Level2 will/will not be equal.
Analyze data from multi-factor, BS, ANOVA IF the interaction were significant
The interaction between Level1 and Level2 was significant, F(df1,df2) = f-value, p=exact p-value or if .000 write p<.001, ETA SQUARED
(We reject the null and accept the alternate hypothesis)
A simple effects test is necessary to determine where the significant differences lie.
How to calculate eta squared
Number of interaction total/number of corrected total
REMEMBER FOR ALL MATH, 2 DECIMAL PLACES
Analyze data from multi-factor, BS, ANOVA IF the interaction were NOT significant
The interaction between Level1 and Level2 was not significant, F(df1,df2) = f-value, p=exact p-value or if .000 write p<.001, ETA SQUARED
(We retain the null hypothesis)
Go ahead and analyze the poc hoc for each of your levels.
6 keys things in creating a graph
- Legend
- Footnotes
- Abscissa
- Ordinate
- Caption that describes contents of the graph, error bars, and sample size
- Origin value is zero
For bar graphs
same rules apply, but also:
- used when levels of IV are categorical, not numeric
2 used for single-factor and multi-factor designs
For single-factor, between subjects SPSS analysis significant
- “The difference among mean”…“DV” ….. was significant, F(df1, df2) = ans, p=exact p=value, if .000, then p<.001, eta squared
- (WE REJECT THE NULL AND ACCEPT THE ALTERNATE HYPOTHESIS)
- Analyze post-hoc test.
- The difference among mean….was significant, p=…..
- The difference among mean…was not significant, p=….
For single-factor, between subject SPSS analysis not significant
- “The difference among mean”…“DV” ….. was not significant, F(df1, df2) = ans, p=exact p=value, if .000, then p<.001, eta squared
- (WE RETAIN THE NULL HYPOTHESIS)
How to calculate expected frequency for chi square in a one-sample case
total number of subjects (N)/by the number of categories (k)
How to calculate expected frequency for chi square in a two-sample case
(rows total)x(column= total)/(total observations)
Df for one-sample case
n-1
Df for two sample case
(rows-1)x(columns-1)
example: 2 rows 2 columns (2-1)x(2-1)= (1)x(1)= =1
Analysis of chi square if greater than critical value found in the table:
Example:
The ……..were significantly different χ²=(df,N=total observations)=computed chi square value, p<.05.
(The computed χ² is greater than the critical value, (write value in parenthesis), at (whatever level, such as .05 level or .01 level)
Analysis of chi square if less than critical value found in the table:
Example:
The ……..were not significantly different χ²=(df,N=total observations)=computed chi square value, p>.05.
(The computed χ² is less than the critical value, (write value in parenthesis), at (whatever level, such as .05 level or .01 level)
For correlation statements
Low weak little
Medium moderate some
High High Strong
Last statement of correlation analysis
The correlation between A and B is/is not significant r(df)=correlation value, p=exact p value or if .000, report as p<.001
What is the only method that can determine causation?
Experiment
T-tests and ANOVAs will have at least how many per group?
30 (for really great power)
Correlations tests require at least how many pairs of measurements to be meaningful
10