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74 Cards in this Set

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When is one-way ANOVA used?
-one DV
-one IV
-three or more levels of the IV

(Can use ANOVA with 2 levels)
What are the 2 sources of variance in the one-way ANOVA
-Treatment variance
-Error variance
What type of size values (large or small) do we want the 2 sources of variance to be
-Treatment variance LARGE
-Error variance small
How is ANOVA represented
"F"

F= Treatment variance/Error variance

the bigger the "F" value, the more likely to reject the null
What does ANOVA stand for
Analysis of Variance
What is the Error variance attributed to
-participants
What can affect the participants
environment: causes participants to react diff when assessed on the DV

history: causes diff. responses to treatment
Equation

Degrees of Freedom for ANOVA
F = MSbetween/MSerror

MS-mean squared
MS = SS/N or SS/N-1

SS: Sum of Squares
N: sample size for population
N-1: sample size for sample
What is the difference between MSb and MSe
with the "b", it is the number of groups (k)-1

with the "e", it is the total number of participants (N-k)
What are the seven steps in ANOVA
1)State the null
2)One-way ANOVA (equation F=)
Assumptions
3)alpha=0.05
4)Criteria for rejecting the null (p<0.05)
5)run the test
6)Accept/reject the null
7)Post Hoc Test
8)conclusion
When do you reject the null for ANOVA
-when there are more than 2 groups only tells us that AT LEAST 2 of the groups are different
What is the Tukey Post Hoc test
Pairwise comparisons between means
What is one of the most used Post Hoc tests
Tukey
-can be used to determine which pair of means are different
-controls against type 1 errors
After using the Post Hoc test, when do you reject the null
if the mean difference (absolute value) is greater than or equal to the Tukey contrast value
When are Bivariate Correlation used
When there are two different variables that have been measured
What would the investigator be interested in with Bivariate Correlation
In determining if there is a relationship between the two variables
True or False

If a relationship is found between variables, that indicates a cause and effect
FALSE

i.e. Height and weight in adults...incr, in weight does not mean an incr. in height
When r=1.00 in correlation...
Considered a perfect positive correlation or relationship between the variables

Scores high/low for both variables
When r=-1.00 in correlation...
Considered a perfect negative correlation or relationship

Score high for one variable, but low for the other
What are used to view relationships between variables
Scatterplots
What is the most common type of correlation
moderately positive/negative correlation
What are the positive descriptors used with correlation
r=1.00 - .80 Strong pos.

r=.80 - .40 Moderate pos.

r=.40 - 0 Weak pos.
What are the negative descriptors used with correlation
r=0 to -.40 Weak neg

r=-.40 to -.80 Moderate neg

r=-.80 to - 1.00 strong neg
In what ways can correlations may be used (3)
1.Determine the relationship between 2 variables
2.Determine the reliability of a measuring instrument
3.Determine the validity of a test
What is assumed with correlation techniques
there is a linear (straight) line relationship between variables
How is assumption with correlation techniques checked
by drawing and looking at the line of best fit
Correlation Techniques

Person Product Moment Correlation
This is a parametric technique that is symbolized by a small letter "r"
Correlation Techniques

Spearman Correlation
This is a nonparametric technique also symbolized using "r"
What are the assumptions for Person Product Moment Correlation
1)one group randomly selected from the population of interest

2)both measured variables be interval/ratio data type

3)Data on each variable must be normally distributed

4)variables must have a linear relationship to each other

5)variances of the two variable must be equal
What is the Homoscedasticity assumption
Assumption asks if the variances of data points are equally distanced from the line of best fit
How do we determine if the Homoscedasticity assumption is met
ellipse shape circles are drawn around the points to decide if assumption is met
What is the seven step procedure for Pearson Product Moment r
1)Write the null
2)get the Pearson Product Moment r formula
3)determine the alpha level
4)Determine the critical value (state when the Ho is rejected)
5)calculations
6)Compare calc. to critical r
7)state conclusion
What is the Coefficient of Determination
=r squared

tells us the proportion of shared variance by the two variables

The amount of variance explained in performance on one variable by knowing the performance on the second variable
What is a synonym for regression
Prediction
What must be done first between X and Y variables
the Correlation
What are soem examples of Regression
-GRE tests predicting individual's success in grad school

-measuring skinfolds to predict body fat %

-determining activity level and measuring BMI
What is the prediction/regression formula
Y'=bX + a

**same formula for a straight line** where "b" is the slope and "a" is the y-intercept
What is the difference between Y and Y'
Y is the actual observed score

Y' is the predicted score
What does the regression line describe
formula for the line describes the line of best fit
How many points are needed to define a line
2
What can be calculated by knowing 2 points in the line
The slope (a) and the y-intercept (b)
True or False

Estimates are made for the line of best fit using all of the data because we do not know the 2 points to begin with
True
what does the slope steepness depend on
how the changes in the X variable (predictor) are related to changes in the Y variable (criterion)
What does the regression line describe
formula for the line describes the line of best fit
How many points are needed to define a line
2
What can be calculated by knowing 2 points in the line
The slope (a) and the y-intercept (b)
True or False

Estimates are made for the line of best fit using all of the data because we do not know the 2 points to begin with
True
What does the regression line describe
formula for the line describes the line of best fit
what does the slope steepness depend on
how the changes in the X variable (predictor) are related to changes in the Y variable (criterion)
How many points are needed to define a line
2
What can be calculated by knowing 2 points in the line
The slope (a) and the y-intercept (b)
True or False

Estimates are made for the line of best fit using all of the data because we do not know the 2 points to begin with
True
what does the slope steepness depend on
how the changes in the X variable (predictor) are related to changes in the Y variable (criterion)
How is the line of best fit drawn
1)Place dot where the mean X score meats the mean Y score
2)locate the y-intercept value
3)connect the two points
True or false

Using the scatterplot and prediction line is a precise way of predicting
False
True or false

Once prediction formula is developed, it is use on individuals who were involved in its formulation
False

Individuals who were NOT involved
What are the X values for each individual entered into
The prediction formula to determine a predicted Y score
What is the minumum number of sujects needed per variable
40
Why is there a minumum requirement of suject with regression lines
half of the subjects are used to develope the regression prediction formula and the other half are used to test the formula

-need to determine if it is a good prediction formula
When are predicitons considered to have NO errors
when r = 1.00 or -1.00
What is error of estimates
residual

the actual Y value minus the predicted Y value
Definition

Variance error of estimate
The variance of a sample of residuals
Definition

Standard Error of Estimate (SEE)
The square root of variance error of the estimate

also-the standard deviation of the residuals
True or False

Want the standard error of estimate to small
True

The smaller it is, the more precise the prediction
What will result in a smaller SEE (standard error of estimate)
small stnd dev for the Y scores and high magnitude for r
Formula

SEE
= sy x (sq rt. of 1-r squared)

sy- stnd dev of Y variable
What are the assumptions for Bivariate regression
Same as correlation
1)Randomness
2)normal distribution
3)linear relationship btwn IV and DV
What is multiple Regression
has more than on IV
What is the general purpose for multiple regression
asses relationship between one variable (DV, symbolized as y) and several others (IVs, predictor, or x)
What can the IV be for multiple regression
-Correlated or not
-Continuous or categorical
-Naturally occurring or manipulated
What is the formula with multivariate regression
Yp=a + b1X1 + b2X2 +.....
Definition

Beta Weights
The standardized regression coefficients (b in the equation)
What are Beta Weights used to determine
the importance of the IV in relation to the DV
True or false

Beta Weights are really the raw regression coefficient (raw score) converted to a z-score
True