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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